Thoughts on open source, cloud native and distributed databases
Team YugaByte was at AWS re:Invent in Las Vegas last week. While AWS was announcing a flurry of new product releases and existing product updates, we had some excellent deep dive conversations at our booth on the future of transactional databases and how YugaByte DB is playing its part in shaping that future. This post summarizes our key learnings from the conference,
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Read MoreLots has happened since our last engineering update about 3 months ago. Below are some of the highlights.
We have made a lot of progress on YSQL, the PostgreSQL compatible distributed SQL API for YugaByte DB! You can also read about YSQL architecture which covers how distributed SQL is implemented in YugaByte DB.
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Read MoreApplication developers usually spend considerable time evaluating multiple operational databases to find that one database that’s best fit for their workload needs. These needs include simplified data modeling, transactional guarantees, read/write performance, horizontal scaling and fault tolerance. Traditionally, this selection starts out with the SQL vs. NoSQL database categories because each category presents a clear set of trade-offs. High performance in terms of low latency and high throughput is usually treated as a non-compromisable requirement and hence is expected in any database chosen.
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Read MoreOur post Getting Started with Distributed Backups in YugaByte DB details the core architecture powering distributed backups in YugaByte DB. It also highlights a few backup/restore operations in a single region, multi-AZ cluster. In this post, we perform distributed backups in a multi-region YugaByte DB cluster and verify that we achieve performance characteristics similar to those observed in a single region cluster.
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Read MoreYugaByte DB is a distributed database with a Google Spanner-inspired strongly consistent replication architecture that is purpose-built for high availability and high performance. This architecture allows administrators to place replicas in independent fault domains, which can be either availability zones or racks in a single region or different regions altogether. These types of multi-AZ or multi-region deployments have the immediate advantage of guaranteeing organizations a higher order of resilience in the event of a zone or region failure.
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Read MorePresto is a distributed SQL query engine optimized for OLAP queries at interactive speed. It was created by Facebook and open-sourced in 2012. Since then, it has gained widespread adoption and become a tool of choice for interactive analytics. It supports standard ANSI SQL, including complex queries, aggregations, joins, and window functions. It has a connector architecture to query data from many data sources such as SQL and NoSQL databases as well as traditional big data platforms such as Hive/Hadoop.
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Read MoreWeb app developers initially adopted MongoDB for its ability to model data as “schemaless” JSON documents. This was a welcome relief to many who were previously bitten by the rigid structure and schema constraints of relational databases. However, two critical concerns that have been a thorn on MongoDB’s side over the years are that of data durability and ACID transactions.
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Read MoreIn this post, we will look at the architecture of YSQL, the PostgreSQL-compatible distributed SQL API in YugaByte DB. We will also touch on the current state of the project and the next steps in progress. Here is a quick overview:
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Read MoreYugaByte’s mission from day one has been to simplify operational database infrastructure. We are doing so by bringing together the best aspects of SQL and NoSQL into a single transactional, high-performance database. I am pleased to announce a key milestone in our mission with the formal introduction of YSQL, YugaByte DB’s PostgreSQL-compatible distributed SQL API, as part of the recent 1.1 release.
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Read MoreACID transactions were a big deal when first introduced formally in the 1980s in monolithic SQL databases such as Oracle and IBM DB2. Popular distributed NoSQL databases of the past decade including Apache Cassandra initially focused on “big data” use cases that did not require such guarantees and hence avoided implementing them altogether. Our post, “A Primer on ACID Transactions: The Basics Every Cloud App Developer Must Know”
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