Apollo raises $22M for its GraphQL platform

Apollo, a San Francisco-based startup that provides a number of developer and operator tools and services around the GraphQL query language, today announced that it has raised a $22 million growth funding round co-led by Andreessen Horowitz and Matrix Partners. Existing investors Trinity Ventures and Webb Investment Network also participated in this round.

Today, Apollo is probably the biggest player in the GraphQL ecosystem. At its core, the company’s services allow businesses to use the Facebook -incubated GraphQL technology to shield their developers from the patchwork of legacy APIs and databases as they look to modernize their technology stacks. The team argues that while REST APIs that talked directly to other services and databases still made sense a few years ago, it doesn’t anymore now that the number of API endpoints keeps increasing rapidly.

Apollo replaces this with what it calls the Data Graph. “There is basically a missing piece where we think about how people build apps today, which is the piece that connects the billions of devices out there,” Apollo co-founder and CEO Geoff Schmidt told me. “You probably don’t just have one app anymore, you probably have three, for the web, iOS and Android . Or maybe six. And if you’re a two-sided marketplace you’ve got one for buyers, one for sellers and another for your ops team.”

Managing the interfaces between all of these apps quickly becomes complicated and means you have to write a lot of custom code for every new feature. The promise of the Data Graph is that developers can use GraphQL to query the data in the graph and move on, all without having to write the boilerplate code that typically slows them down. At the same time, the ops teams can use the Graph to enforce access policies and … Read the rest

Qubole launches Quantum, its serverless database engine

Qubole, the data platform founded by Apache Hive creator and former head of Facebook’s Data Infrastructure team Ashish Thusoo, today announced the launch of Quantum, its first serverless offering.

Qubole may not necessarily be a household name, but its customers include the likes of Autodesk, Comcast, Lyft, Nextdoor and Zillow . For these users, Qubole has long offered a self-service platform that allowed their data scientists and engineers to build their AI, machine learning and analytics workflows on the public cloud of their choice. The platform sits on top of open-source technologies like Apache Spark, Presto and Kafka, for example.

Typically, enterprises have to provision a considerable amount of resources to give these platforms the resources they need. These resources often go unused and the infrastructure can quickly become complex.

Qubole already abstracts most of this away, offering what is essentially a serverless platform. With Quantum, however, it is going a step further by launching a high-performance serverless SQL engine that allows users to query petabytes of data with nothing else but ANSI-SQL, giving them the choice between using a Presto cluster or a serverless SQL engine to run their queries, for example.

The data can be stored on AWS and users won’t have to set up a second data lake or move their data to another platform to use the SQL engine. Quantum automatically scales up or down as needed, of course, and users can still work with the same metastore for their data, no matter whether they choose the clustered or serverless option. Indeed, Quantum is essentially just another SQL engine without Qubole’s overall suite of engines.

Typically, Qubole charges enterprises by compute minutes. When using Quantum, the company uses the same metric, but enterprises pay for the execution time of the query. “So instead of the … Read the rest

Microsoft brings Azure SQL Database to the edge (and Arm)

Microsoft today announced an interesting update to its database lineup with the preview of Azure SQL Database Edge, a new tool that brings the same database engine that powers Azure SQL Database in the cloud to edge computing devices, including, for the first time, Arm-based machines.

Azure SQL Edge, Azure corporate vice president Julia White writes in today’s announcement, “brings to the edge the same performant, secure and easy to manage SQL engine that our customers love in Azure SQL Database and SQL Server.”

The new service, which will also run on x64-based devices and edge gateways, promises to bring low-latency analytics to edge devices as it allows users to work with streaming data and time-series data, combined with the built-in machine learning capabilities of Azure SQL Database. Like its larger brethren, Azure SQL Database Edge will also support graph data and comes with the same security and encryption features that can, for example, protect the data at rest and in motion, something that’s especially important for an edge device.

As White rightly notes, this also ensures that developers only have to write an application once and then deploy it to platforms that feature Azure SQL Database, good old SQL Server on premises and this new edge version.

SQL Database Edge can run in both connected and fully disconnected fashion, something that’s also important for many use cases where connectivity isn’t always a given, yet where users need the kind of data analytics capabilities to keep their businesses (or drilling platforms, or cruise ships) running.

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