2020 has been quite an unusual year. Many aspects of business and life have been radically transformed. Words can’t fully express the suffering experienced this year as individuals, families, societies, and as a global community. But simply put – 2020 was challenging and hard. We wish everyone a kind and gentle new year ahead.
As we eagerly welcome 2021, we also wanted to take a moment to wrap up 2020 at Yugabyte. Amid all the tough spots,
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At the Distributed SQL Summit 2020, Ken Owens – Vice President, Cloud Native Engineering, Mastercard, presented the talk, “The Data Divide: An End User’s Cloud Native Journey to Distributed Databases.”
Because Ken has been working at the intersection of technology and financial services for more than 20 years, he brings a unique perspective to how cloud native and distributed systems can transform, what from the outside may appear to be a slow moving industry,
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Our mission at Yugabyte is to build the default distributed SQL database for cloud native applications in a multi cloud world. We recently announced the general availability of Yugabyte 2.5, which brought new features like Geo-Partitioning and Enterprise-Grade security features in addition to major enhancements in multi-region deployments and performance – while also improving on high availability, horizontal scalability, and ease of managing the database. The Yugabyte team is currently working on even more exciting features,
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Welcome to this latest post on what’s new and improved in YugabyteDB Docs! We’re continually adding to and updating the documentation to give you the information you need to make the most out of YugabyteDB.
As a reminder, YugabyteDB provides two distributed SQL APIs:
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This blog post is written by guest author Bhavin Gandhi, Software Engineer at InfraCloud Technologies, Inc., in collaboration with the teams at Buoyant, the creator of Linkerd, and Yugabyte.
As more organizations turn to microservices architectures for their applications, Kubernetes naturally emerges as a perfect complement to those applications. But for application developers, building on Kubernetes can introduce complex problems to solve at the application layer. This is where service meshes like Linkerd come to the rescue and provide essential features like reliability,
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We were delighted to have Joe Hellerstein, professor of Computer Science at UC Berkeley and co-founder and Chief Strategy Officer at Trifacta, give the day 2 opening keynote at this year’s 2020 Distributed SQL Summit.
If you weren’t able to attend or want a refresher, here’s the summary and playback of his keynote presentation.
Joe presented the the art of the state serverless computing and distributed data in four chapters:
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At the Distributed SQL Summit 2020, Tobias Meixner – CTO & Co-Founder at BRIKL, presented the talk, “A Migration Journey from Amazon DynamoDB to YugabyteDB and Hasura.”
Switching databases is painful, even more so when going from NoSQL to SQL. In this talk Tobias gave us insights into BRIKL’s two key elements of their migration path. First, migrating from Apollo Server and Amazon DynamoDB over to Hasura and YugabyteDB.
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Manetu uses YugabyteDB to support its Consumer Privacy Management (CPM®) platform, a microservices application that needed fine-grained transaction support, secondary indexes, and triplestore capabilities, all while being able to scale to billions of encrypted identities.
At a recent Distributed SQL Summit, Travis Logan – CTO & Co-Founder at Justuno, presented the talk, “Evolve: A Database Journey from Ground to Cloud.”
With over 14 years of experience with Microsoft SQL Server, Travis is well-versed in the evolution of transactional databases. In this talk he summarizes his experiences with traditional RDBMS while trying to improve their redundancy, scaling characteristics, and performance.
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YugabyteDB is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner. YugabyteDB uses its own special distributed document store called DocDB. But it provides SQL and stored procedure functionality by re-using the “upper half” of the standard PostgreSQL source code. This is explained in the two part blog post “Distributed PostgreSQL on a Google Spanner Architecture”: (1) Storage Layer; and (2) Query Layer.
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