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Developers can use the Redis-like interface with the Macrometa platform

Redis is one of the most popular open-source in-memory data stores today, named the “Most Loved” database by Stack Overflow for five consecutive years. This year it lost that position to PostgreSQL.

Because of its fast performance, Redis is a popular choice for:

Developers can use the Redis commands with Macrometa and still automatically synchronize data between various locations worldwide in milliseconds.

It can interact with the Macrometa platform in various ways, using a console, an API call, or an SDK. Redis supports both JavaScript and Python SDK.

In the example below, we are using Python SDK to SET string key-value pairs:

In our application we need to retrieve data, we can do that with GET Redis command as shown below:

In this case data is stored on the platform collection in this format:

Keep in mind that expireDate is an optional parameter.

The Redis collection that we created is automatically synchronized across various locations around the world, up to over 175 locations. This leads to low latency times. Developers don’t need to worry about infrastructure and they can use well-known Redis commands they are already familiar with so there is no learning curve.

, and documentation to quickly get started with Macrometa. Sign up for a 

Macrometa Tutorial: Redis As An Interface 

Enterprises are challenged to deliver fast response times when data requests travel to and from the faraway cloud. Bringing your data to the edge and caching data closer to where it originates and where it is needed can provide lower latency and reduce costs. This blog will outline key sections from our 

, including why and what you should cache, the key components of a real-time, geo-distributed, and replicated cache, and how the Macrometa Global Data Network (GDN) supports caching.

With edge computing, information can be cached at 

 locations worldwide, so applications can access data faster with less latency.

Caching can reduce your database load and decrease overprovisioning instances to drive costs down significantly, as many databases charge for throughput. Processing and computing can be done closer to the originating device by caching data at the PoPs, with a lot less backhaul network to the cloud.

The question should be: what does the PoP need to avoid sending a request to a central hub before replying to a user request? A few common choices are specific rows of recent data from 

, API results to access globally shared data, and configuration files for user applications. If we look at food delivery as an example, you may want to cache static map information, route calculations, and any metadata about the deliveries that are frequently accessed.

Key components of a real-time, geo-distributed & replicated cache

It makes sense that a real-time, geo-distributed, and replicated 

 has to be fast and have a wide geographic reach, but let’s go over all the key attributes in detail. 

 that can handle data in any format from traditional databases and data streams for unstructured data in a unified manner.

 for real-time information that needs to be transmitted almost immediately - an edge cache needs to allow a PoP to enable quick responses for time-critical tasks.

 - since the stateless and distributed concepts of 

 complement the edge's enhanced reachability and networking capabilities.

that can handle a geographical subset of clients anywhere in the world.

 and limit where data travels, thus conforming to regulations like GDPR.

 was designed to support a real-time, geo-distributed, and replicated edge cache. The image below shows how two PoPs communicate through streams handled by Conflict-Free Replicated Data Types (CRDT) resolution. At the top, various queries enter in different formats and protocols. The in-memory cache in each PoP responds quickly to client requests. Let’s walk through other features that help enable a real-time, geo-distributed and replicated cache.

 and enables users to access the same copy of data via multiple interfaces. You simply use different databases at the same endpoint - so it is much easier to integrate different data streams into an application.

In-memory side cache with disk-based persistence

Applications can retrieve data immediately without needing even to access a disk, much less send a request over the network. The data is written to disk so that it will survive in the case of a hardware failure, and the cache can be restored to a new or restarted node. 

Hyper-distribution across several regions

Macrometa maintains more than 175 PoPs scattered through many different regions. Macrometa also 

 with telecom companies to use its facilities to provide geographic flexibility to its clients. Two key features in the GDN that enable rich hyper-distribution of cache across several regions are:

CRDT model: The Macrometa GDN uses a CRDT update model. Each PoP logs all the changes it makes to its cache and sends these changes out to every other PoP at regular intervals. These data transfers are called streams, and instead of hub-and-spokes, CRDT creates peers. PoPs send out these compressed and encrypted streams frequently, and each stream contains just data for a few seconds, so it is not a network burden.

Coordination-free garbage collection: Each PoP can independently send, receive, and process data at its own rate without acknowledging or waiting for other points of presence. The coordination-free architecture can be leveraged for efficient garbage collection - timely truncation of logs to remove old entries.

 feature allows you to use a subset of regions, all based on your own criteria and not pre-generated (such as US, Europe, or Asia). GeoFabrics helps you comply with local data regulations (such as GDPR) and reduce read/write costs associated with global replication. GeoFabrics offers more options for storing or accessing data - with a simple on/off switch.

Standardized “Redis-like” cache interface

The GDN cache interface is similar to common caching solutions, so you can quickly get started and implement real-time, geo-replicated caches for your applications. If your application presently uses a cloud-backed cache to serve users, you can easily extend your use cases with the GDN to make your apps ready for the edge.

A geo-distributed and replicated cache can support use cases like real-time dynamic advertising, or any app with real-time user expectations. Download this 

for more details about caching data closer to your customers, partners, suppliers, and staff at the edge.

Faster Apps At The Edge With A Geo-Distributed & Replicated Cache

, data is processed closer to the source of the data at the edge of a network. This can be particularly useful for gaming companies in a few different ways:

Reduced latency: By processing data closer to the source, edge computing can help reduce latency and improve the overall performance of games.

Improved network performance: Edge computing can help reduce the load on central servers and improve network performance, especially in areas with a high density of players.

Enhanced security: Edge computing can help protect against cyber threats by processing and analyzing data locally rather than sending it over the internet to a central server.

Better scalability: Edge computing can help gaming companies scale their systems more efficiently, allowing them to add processing power closer to the data source.


Take Your Gaming to the Edge: Unlock the Ultimate Gaming Experience with Macrometa

Edge computing is rapidly emerging as the go-to technology for businesses requiring the highest performance, scalability, and security levels. This includes gaming applications requiring the best 

, response time, and data processing power. Macrometa’s edge computing platform is leading the way in 

 on edge, allowing gamers to unlock the ultimate gaming experience. Here’s a look at how edge computing is revolutionizing gaming and how Macrometa is taking it to the next level.


Macrometa’s edge computing platform is leading the way in gaming on edge. The platform is designed to provide gamers with the ultimate gaming experience by reducing latency, improving response times, and providing a layer of security.


It provides gamers with the highest levels of security. Gaming applications can keep data secure by processing data at the edge and preventing it from being shared with third parties. This can help protect gamers’ data and ensure that it is only used for the purposes intended.

To learn more about Macrometa’s edge computing platform and how it can revolutionize gaming, check out 

 on YouTube. In this video, Alan (our Principal Technologist) showcases a first-person shooter game demo with real-time insights and a liveops dashboard on the Macrometa platform.


From this demo, you’ll learn how edge helps gaming and esports companies keep gamers engaged and maintain gamers' experience at a global scale while managing in-game data. You can also know more about:

Gaining insight into the gamer journey and experience

How to maintain gamer experience at scale

Gain insight and control game mechanics in real-time

At Macrometa, we’re committed to providing gamers with the best in gaming on edge. Our edge computing platform is designed to provide gamers with the ultimate gaming experience by reducing latency, improving response times, and providing a layer of security.


Check out the tutorials, QuickStarts, and 

 to quickly get started with Macrometa. You can actually build a streaming app in 10 mins or less! Start with a 

Enhanced Gaming Experience on Edge: Macrometa in Action

No one’s an expert at anything right away. Whether learning a new language, programming, or learning how to navigate a new platform (like Macrometa), practice makes perfect.

At Macrometa, we’re helping developers build real-time apps and APIs in minutes. If you want to become a Macrometa expert, we have these resources that can help.

One of the easiest ways to learn a new skill is to talk to others. That’s why we created our Macrometa Community Slack for anyone to come and chat about projects, ask questions, and much more. We have super users and people from the Developer Experience, Product, and Customer Success teams ready to help.

We’ve designed a Quickstart Guide in our docs to help jumpstart your Macrometa journey. It’s designed to help you learn the basics of creating a collection and running a query using some sample data. In less than 15 minutes, you can learn about Macrometa Query Workers and build an address book with full search capabilities.

We have a whole library of sample applications demonstrating what you can do with the Global Data Network. Build a streaming ETL application, a crypto trading bot, an online store, or an app that detects credit card fraud. Step-by-step tutorials with sample code hosted on GitHub.

Some of us are visual learners, so we’ve started building some great video content and tutorials on Youtube for easy access. We have 10-minute demos and tutorials, case studies, and webinars, so don’t forget to smash that like button, comment, subscribe, and click on the bell.

Macrometa unlocks amazing workflows around real-time data. If you’re a developer looking for a NoSQL database that does a whole lot more or someone wanting to get real-time insights from data around the globe, sign up for a

and let us know on the community slack. There might be a t-shirt in it for you.

How to become a Macrometa Expert

2022 has been an eventful and exciting year for Macrometa. From product launches to new strategic partnerships, SOC 2 compliance, and a virtual Developer Week, we’ve had a lot of achievements to celebrate with our customers.

In this blog post, I’ll outline Macrometa’s 2022 year in review, our many successes, our plans for 2023, and our ambitious vision for the future to help our customers move their business forward.

The year 2022 has been an excellent success for Macrometa and its customers. We developed our ground-breaking edge computing platform, which has enabled us to provide powerful, secure, and reliable data solutions to our customers. Additionally, we released our enterprise-grade data management solutions, which are designed to help businesses better manage their data and quickly gain insights. Here are some highlights:

One of the proudest moments for Macrometa from 2022 was achieving the SOC 2 certification.

In a fully-distributed world that processes information milliseconds, we must instill confidence in our data policies and security. This certification is a huge milestone for Macrometa and the culmination of months of hard work and dedication toward the security of our platform.

Learn more about how we're committed to keeping data safe in the SOC 2 

announcement from Macrometa CISO Eddie Garcia.

Current 2022, the next-generation Kafka Summit

 in Austin, Texas, October 4-5. This was the first-ever data streaming industry event, and we were grateful to have met real-time data experts worldwide.

Akamai and Macrometa partner to create an Edge Cloud Super Platform for Enterprise Developers. Akamai cloud computing based on Linode and EdgeWorkers edge computing technology combined with Macrometa's Global Data Network (GDN) will help enterprise developers build, deploy, and run global apps and APIs seamlessly across edge and cloud.

DevCycle partnered with Macrometa to launch the the world's first and fastest Feature-Flag-as-a-Service (all from the Edge). 

 about why they chose Macrometa and how they built an ultra-low-latency global feature flags solution using Macrometa.

Hosted a virtual Developer Week and released demo videos

Macrometa hosted a week-long Developer Week from November 7th - November 11th, 2022, where developers could see real-life use cases in action, build a streaming app in minutes, and explore the 2023 roadmap.

This week-long online virtual event focused on enterprise developers interested in building the next generation of globally-distributed, real-time applications and APIs. It features tutorials and guides from partners like Akamai and Dish Networks and customers AppSecEngineer, and DevCycle, to name a few. During Developer Week, Macrometa hosted technical content workshops and demos for real-time apps and APIs for web, mobile, IoT in SaaS, Web Services, developer tools, multiplayer gaming, video streaming, e-commerce, manufacturing, and more.

Watch all the demo videos and developer week content

We launched a public Slack Community for our users to engage with each other and with product experts at Macrometa. We’re hoping it will become a place where our community helps each other solve problems and share best practices.

Throughout 2022, we’ve been focusing on creating content to help our prospects, developers, and customers learn more about Macrometa and its solutions.

Some of the webinars that we launched in 2022:

Complex Event Processing: What’s After Apache Spark and Apache Flink

 we compare Macrometa's CEP and streaming analytics platforms like Spark and Flink to help you determine which solution best matches your use case. Learn about the difference between streaming analytics and CEP and how to get the most value from your data.

The Edge of Retail: Enabling Real-time Inventory Management

 to learn more about how real-time inventory management can boost profits and improve customer experiences. The experts at Macrometa explain how edge computing brings the power of real-time visibility to retail operations. 

Watch any of these webinars on demand at your convenience and reach out if you have any questions.

Unraveled Macrometa’s New UI And Design Process

Macrometa Head of Design - Dustin Larimer shares a peek into his team’s effort to craft a new visual aesthetic, brand system, and design system. Read more about the new UI 

At Macrometa, our vision is to be a leader in GDN & edge computing, and data management solutions. Our goal for 2023 is to continue to drive innovation in data management solutions and to provide our customers with access to our powerful and reliable data solutions. We also want to continue expanding our strategic partnerships, exploring new opportunities, and building on our existing partnerships.

We released our product roadmap highlights during Developer Week. 

 as our Product team gives a preview of some of the exciting things to come in 2023. 

We are confident that 2023 will be an exciting and successful year for Macrometa. We look forward to continuing to provide our customers with the utmost powerful solutions.

If you're interested in testing new features, reach out to me at justin@macrometa.com.

Inside Macrometa 2022, And A Blazing Start To An Excitingly Futuristic 2023!

Everyone is familiar with major cloud providers’ regions and what happens to businesses when a main location goes offline or has poor performance. It can have a lasting economic impact across the country or multiple countries. Once a customer can’t order food service, find a ride, get directions, or make a purchase, they may choose not to use your business again. We live in a real-time world where the demand is no longer in minutes or seconds, but in the milliseconds. Points of access have become more critical - as we are soon challenged with managing 

 is built upon Points of Presence (PoPs) - data centers located in strategic geographical locations around the globe. These data centers serve as a point of access to enable organizations to build distributed applications and services with incredibly low latency. Let’s walk through more details about PoPs and Macrometa’s GDN. 

 is a physical location, or an artificial demarcation point, that connects sites or communication 

. To access the internet, a PoP communicates with the network access point which is the point where networks exchange access requests.

When a user requests access, that request goes to the nearest PoP to the user. So if you are in Atlanta, the Atlanta PoP would respond to that request. The access request reaches internet exchange points where the information is then exchanged and the user gets access to peer between networks.

Generally speaking, the larger the PoP network, the less latency there is, resulting in a better user experience. If there is a data center connection failure at the nearest PoP, the request can be rerouted to the next closest PoP with no service interruption. The latency difference may be barely noticeable if the next closest PoP is still in a similar region.

The Macrometa GDN is available in over 175 cities - or PoPs around the world. Macrometa puts data into action and delivers real-time and event-driven apps and data into more than 2B users and 10B devices in 50ms. Our global PoPs can act as a 

 on top of five different service providers that include cloud providers, telecom providers, and CDNs. Our service provider 

 include Akamai (who acquired our partner Linode), Cox Edge, AWS, and Google Cloud. Because the GDN is on top of routes and capacity provided by transfer providers who have different economics and pricing than typical cloud providers, it can result in significantly less costs than the cloud. Plus, the diversity means you don’t have to worry about outages with one provider - or in one location - affecting your bottom-line. 

More control over data location, compliance, and costs

With Macrometa, you can create fabrics for multiple regions in the GDN. The 

 feature allows you to use a subset of regions, all based on your own criteria and not pre-generated (such as US, Europe, or Asia). GeoFabrics helps you comply with local data regulations (such as GDPR) and reduce read/write costs associated with global replication. GeoFabrics offers more options when data should be stored/accessed - with a simple on/off switch. With GeoFabrics, you can just select the regions you need and Macrometa will handle all of the operations.

The flexibility to choose your cloud environment

With Macrometa, you can choose our cloud with the GDN PoPs, or choose a multi-cloud or hybrid cloud where you're on-prem and in the cloud. Or you can deploy Macrometa in a virtual private cloud or in your on-prem data centers - to leverage your existing investments or adhere to company or local security policies. If you are currently using a specialized cloud provider, have contractual obligations with an existing provider, or would like a service outside of our 175+ PoPs, you can work with Macrometa to include them in your network.

Akamai EdgeWorkers technology combined with Macrometa GDN

 enables enterprise developers to build, deploy, and run applications and APIs across the edge and the cloud. Developers will have access to the Akamai network, which includes hundreds of public cloud regions covering Linode, Akamai Cloud Computing, as well as AWS, GCP Azure, and telecom 5G networks.

 can meet modern performance demands in a geographically distributed system. If you want to see Macrometa in action, 

Driving Low Latency With Global PoPs

Games need the right platform and protocol for fast reaction times. The edge offers smoother gameplay and less lag. It can also simplify management and reduce costs compared to the cloud or servers.

Let’s run through the advantages of the edge and compare TCP and UDP protocols. Then we will go over the Macrometa for Gaming solution and how you can get started.

 or data centers for scale and management. Traffic delays with the cloud or faraway servers can degrade cross-play or cross-save gaming experiences. At the 

, you can store and process data close to your players - resulting in better response times. Common cloud providers can be expensive as your data volumes increase. Backend servers need time and resources for set-up, maintenance, and updates.

TCP connects players around the world. It is a reliable, connection-oriented protocol that provides error checking and flow control. Many online games use TCP for network communication and to keep data secure. Real-time strategy, multiplayer online role-playing, chess, and puzzle video games are often TCP-based. Some multiplayer first person shooter games and 

The main difference between TCP and UDP is that TCP is connection-oriented while UDP is not. TCP requires a three-way handshake to establish a connection before data can be sent, and UDP does not have this requirement.

UDP is popular due to its low overhead and its ability to send data quickly and efficiently. It is often used for first-person shooters, racing and sports titles, and massively multiplayer online role-playing games when faster response times are required. Not all games need the same response times and TCP is still a good option in many situations.

With over 175 points of presence (PoPs), Macrometa enables multi-region gaming efficiencies. Data is automatically replicated across the Global Data Network (GDN). API requests are routed to the nearest available location. Updates at any location propagate across the network and bring all nodes to parity within milliseconds. Macrometa’s geo-distributed, real-time data layer is available within 50ms of 80% of the global population. This allows you to 

You can maintain a persistent state using different types of data within the Macrometa 

 and event & log capture to streamline development. The GDN also provides an 

 layer that’s deeply integrated directly with the data layer itself - that brings compute to where the data is originating, or the data is being consumed.

By using a single platform with analytics, you can have a clear view of all gaming activities. Spot early trends and recognize patterns to create business opportunities or prevent threats. For example, you can detect lag switches, or prevent bad actors from stealing gamers' information. Use 

 to check game health and gamer activities. Create new revenue programs and personalize gamers’ experience with real-time leaderboards and incentives.

Currently, Macrometa supports TCP for dynamic data. If UDP support is needed, a microservice can be created that connects to the Macrometa GDN.

 to quickly get started with Macrometa. I mean you can actually build a streaming app in 10 mins or less! Start with a 

How to Create Better Gaming Experiences on the Edge

A fascinating fact about the octopus - they create these elaborate, ocean floor dens with shells and shiny treasures they find along the way. All of these pieces – bottle caps, coconuts, shells, rocks, coral, pieces of shipwrecks – are collectively known as an Octopus’s Garden. I believe some young lads from Liverpool might have talked about it once.

The interesting part is that although these little garden cities sound like a magical Octlantis, Octopus are a hell of a lot more than interior decorators. They use the shells as tools for gathering food or as a door to thwart intruders, they use them as support structures to give their dens strength and rigidity, and they’re used as landmarks - all kinds of utilitarian brilliance out of different pieces.

In a previous post, we touched a little on the similarities between the 

 For one, there’s no single point of failure. The octopus in its profound design has multiple hearts, a brain in each arm that acts independent of the others. It’s a beautifully crafted, natural redundancy that we felt drawn to. Macrometa, after all, has a decentralized architecture that makes us, like this humble cephalopod, both highly fault tolerant and resilient. 

It also reminded me of the ecosystem we’re building with our partnership community. The way Macrometa plays well with other tools. From an architectural standpoint, I think about the Global Data Mesh and the ability to filter in data from all of these little pieces everywhere. Every data source, every event, every PoP, every API - are all important pieces of the octopus garden. This foundation provides tools for developers to remedy their previously unsolvable problems with low latency at the edge.

[This isn’t an endorsement for intelligent design, not in the slightest, but isn’t it amazing how these parallels are all designed so intelligently]

 is a full-stack edge platform for building and running applications at the Edge. The GDN “garden” consists of a Global Data Mesh, Edge Compute, and Data Protection.

Global Data Mesh: Real-time, geo-distributed storage layer

Historically, database management and storage has been the bane of IT. As the ocean of data ebbs and flows in all directions, developers and enterprises and everyone that relies on data for decisions need a simplified way to quickly address different types of data. The 

 has all the benefits of a NoSQL database with KV, doc, and graph stores – but the garden is even richer than that. 

Edge Compute: Run real-time apps close to your customers

Macrometa’s Edge Compute puts data into action and delivers real-time and event-driven apps and data globally in <10ms.* The shiniest tools in this garden are 

. Query Workers let developers create simple REST APIs on top of the data mesh. Stream Workers enables Complex Event Processing functions and Stream Processing workloads - in minutes instead of days or months.

Customers tell us that the combination of tables and streams integrated within Macrometa and the ability to use Stream Workers to process data live is “the Holy Grail” for app development. 

Organizations need to comply with regulatory and legal compliance standards. Macrometa’s Data Protection supports geo-pinning or geo-fencing to address data sovereignty use cases. Developers and operations can easily set up 

 for regional and global data, and adjust locations with just a toggle. 

 and offers user, token-based, and API keys 

. It encompasses privacy, security, governance – the healthy tenets of a “security garden” I suppose. Hmm, maybe we should’ve called it a security garden. 🤔

 that create the gardens are considered “ecosystem engineers.” They’re called this because they create and transform their environments, improving resource availability for everyone in the community. At Macrometa we team up with partners to give our developers flexibility and speed. The Global Data Mesh connects data so that it can be stored, accessed, and processed at lightning speed, regardless of where it lives. We chose a mascot that was already doing the things we aspired to do.

Our goal is to give developers the freedom to build and run applications anywhere. We can work within their existing platforms like 

, and even get their applications over that “last mile” with partners like 

 with just a simple service API. Once you’ve built an impossible app, do Feature Flags in real-time thanks to our recent 

 partnership launching the world’s first and fastest Feature-Flag-as-a-service (from the Edge). 

As a company, we’ve prided ourselves on working well with others, and in the process we’ve created many gardens. The point is that they make things stronger, they add resilience, and we continue to explore new ways of seamlessly integrating the “shells” and “shiny objects” that make up the development landscape.

Create your own octopus garden and build the next impossible app. Sign up for a 

We look forward to making some exciting announcements in the next few weeks and would love for you to build with us.

A Data Mesh Is The New Octopus Garden

Originally published 11/1/2022 by Corey Quinn, Chief Cloud Economist at The Duckbill Group, as a Screaming in the Cloud podcast, episode 405, “

Computing on the Edge with Macrometa’s Chetan Venkatesh.

Chetan Venkatesh, Macrometa CEO and Co-founder chatted with Corey Quinn to define the edge and how the edge is “new kind of distributed cloud.” Developers can build apps in a distributed way with Macrometa’s Global Data Network that you “just can’t do in the cloud anymore.” In his chat with Corey, Chetan runs through the need for a consistent data view, the layers of the Macrometa Global Data Network, typical use cases, and how Macrometa is helping developers lower their carbon footprint with more efficient coding and tools.

The term “edge” has been applied across many aspects of IT, especially around 5G technologies. The recent hype is not surprising, when you consider that edge-related annual revenue has been predicted to grow to nearly $274B in 2025 by 

. During the podcast, Chetan clarifies the term edge with a specific definition and indicates there are three different types.

Chetan indicated the edge is “very different from the cloud” when you consider “...that the cloud is defined by centralization, i.e., you’ve got a giant hyperscale data center somewhere far, far away...where you run things at scale and somebody else manages them for you.”

In contrast, “the edge is actually defined by location” and here are the three types per Chetan. And these three types “are now becoming important as a place for you to build and run enterprise apps.”

The first is the Content Delivery Network (CDN) edge and Chetan describes how this is historically “where we’ve been trying to make things faster with the internet and make the internet scale.” Akamai created the 

 “that allowed the web to scale….that’s the first location that defines the edge…where a lot of the peering happens between different network providers and the on-ramp around the cloud happens.” Akamai and Macrometa are working closely together to 

 and Akamai made quite a few appearances during our recent 

“The second edge is the telecom edge. That’s actually right next to you…because every time you do something on your computer, it goes through that telecom layer. And now we have the ability to actually run web services, applications, data, directly from that telecom layer, “ Chetan relayed to Corey. Macrometa works closely with telecom providers like 

The third edge is something that is ready and available at your fingertips and you take it everywhere -your mobile device! Per Chetan, “it’s your internet gateway” and “where you have some compute power, but it’s very restricted and it only deals with things that are interesting or important to you as a person.”

Consistent view of data anywhere in the world

 was originally designed for economies of scale by having data in a centralized location and to make it easy to add or change technologies. However, the cloud does present some challenges that Chetan talks about like how do you “take data and chop it into 50 copies and keep it in 50 different places on Earth.. then keep all those copies in sync?.. So you start to deal with some very basic computer science problems like distributed state and how do you build applications that have a consistent view of that distributed state?..”

 for this issue has to cover three areas: “a way for programmers to do this in a way that doesn’t blow their heads with complexity, a way to do this cheaply and effectively enough where you can build real-world applications that serve billions of users concurrently at a cost point that actually is economical and makes sense, and third, a way to do this with adequate levels of performance where you don’t die waiting for the spinning wheel on your screen to go away.”

Introduction to the Macrometa Global Data Network

 is based on cutting edge computer science incorporating new ideas and research in the areas of messaging, event processing, data consistency, and replication. The Macrometa GDN has 

: a Global Data Mesh that is a real-time, geo-distributed storage layer, an Edge Compute layer to process data to run real-time apps close to your customers, and a Data Protection layer to help organizations comply with regulatory and legal standards.

 has all the benefits of a NoSQL database with KV, doc, and graph stores - plus Macrometa Streams with Pub/Sub and messaging queues. What separates Macrometa from other data storage solutions is that it brings compute closer to people and where data is generated, regardless of where that is. 

Organizations need a consistent view of data, even if multiple copies are sitting all around the world. Say you are a large retail distribution company and folks are ordering from your site, you need 

Chetan explains to Corey that programmers need to be able to operate, modify, and replicate that data with consistency guarantees and high levels of performance. Edge computing and the Macrometa platform “literally puts data and applications within 50 milliseconds of 90% of humans and devices on Earth.” This may seem like a new paradigm, but Chetan indicates it is more of a continuum. The Macrometa platform “feels very much like 

Data comes in different forms and developers don’t have the time to reformat data. Macrometa “provides continuity by looking like a key-value store like Redis” and has “a streaming graph engine built into it that kind of looks and behaves like a graph database, like Neo4j.” Macrometa can distribute and sync data across hundreds of locations but “it looks like a conventional NoSQL 

Plus, Macrometa provides an ACID-like consistency and can support changes (like read and update requests) when you’ve apps running in 100s of locations and each of those places is modifying the same record.

Chetan explains a typical example of organizations with multiple locations. “We have the ability to connect data sources across all kinds of boundaries; you’ve got some data in Germany and you’ve got some data in New York. How do you put these things together and get them streaming so that you can start to do interesting things with correlating this data?”

Another example is when organizations need to collaborate with supply chain or other partners in real-time to address a supply shortage or distribution issue. With the Global Data Mesh you can, “very quickly connect data wherever it might be in legacy systems, in flat files, in streaming databases, in data warehouses,” per Chetan. Macrometa has “500-plus types of connectors.”

But it is not only about getting the data 

 - it is making the data fungible with APIs. “Because the minute you put an API on it and it’s become fungible now that data has actually got a lot of value. And so the data mesh is a way to very quickly connect things up and put an API on it. And that API can now be consumed by front-ends, it can be consumed by other microservices, things like that,” Chetan describes the instant benefits of building APIs on top of the Global Data Mesh.

As Chetan relays to Corey, the GDN also “provides an [Edge] Compute layer that’s deeply integrated directly with the data layer itself. So think of it as Lambdas running stored procedures inside the database… We’ve built a very, very specialized compute engine that exposes containers in functions as stored procedures directly on the database.” You can easily build apps in Python, Go, or the 

 that lets developers create simple REST APIs on top of the data mesh and 

 enables Complex Event Processing (CEP) functions and Stream Processing workloads. 

Macrometa has a compute runtime “that is Docker compatible, so it runs containers,.. it’s Lambda-like,.. so it runs functions.” You can build stateful microservices that can interact with data locally and “then schedule them along with the data on our network of 175 regions.” Chetan goes on to provide some examples of building distributed apps on the GDN.

With a cloud provider, your microservices back-end for a banking, HR 

 app may run in a specific region or two like us-east-1 and Virginia. In the Macrometa GDN, it will potentially run in 15, 18, or even 25 cities - where your end-users are located. If you are ingesting data from an electricity grid in 15-20 cities for 

, you can do all of that locally with Macrometa.

“So that’s what the edge functions does, it flips the cloud model around because instead of sending data to where the compute is in the cloud, you’re actually bringing compute to where the data is originating, or the data is being consumed, such as through a mobile app,” Chetan explains the key benefits of Macrometa vs a typical cloud model.

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