Thoughts on distributed databases, open source and cloud native
In case you missed the news earlier this Summer, YugaByte raised an additional $16M of funding from Dell Technologies Capital and our previous investor Lightspeed Venture Partners. With the additional funding, we are accelerating investments in engineering, sales, and customer success to scale our support for enterprises building business-critical applications in the cloud.
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Read MoreWhether it be a WordPress website’s MySQL backend or Dropbox’s multi-exabyte storage system, data replication is at the heart of making data durable and available in the presence of hardware failures such as machine crashes, disk failures, network partitions and clock skews. The basic idea behind replication is very simple: keep multiple copies of data on physically isolated hardware so that the failure in one does not impact the others and as a result,
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Read MoreWhen creating a Cassandra-compatible YCQL table in YugaByte DB, you are required to create a primary key consisting of one or more columns of the table. Primary key based retrievals are efficient because YugaByte DB automatically indexes/organizes the data by the primary key. However, there are many use-cases where you may need to retrieve data using columns that are not a part of the primary key.
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Read MoreAfter billions of dollars in capital expenditure and reference customers in every major vertical, Google Cloud Platform has finally emerged as a credible competitor to Amazon Web Services and Microsoft Azure when it comes to enterprise-ready cloud infrastructure. While Google Cloud’s compute and storage offerings are easier to understand, making sense of its various managed database offerings is not for the faint-hearted.
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Read MoreOur post 6 Signs You Might be Misunderstanding ACID Transactions in Distributed Databases describes the key challenges involved in building high performance distributed transactions. Multiple open source ACID-compliant distributed databases have started building such transactions by taking inspiration from research papers published by Google. In this post, we dive deeper into Percolator and Spanner, the two Google systems behind those papers,
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Read MoreAs described in A Primer on ACID Transactions, first generation NoSQL databases dropped ACID guarantees with the rationale that such guarantees are needed only by old school enterprises running monolithic, relational applications in a single private datacenter. And the premise was that modern distributed apps should instead focus on linear database scalability along with low latency, mostly-accurate,
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Read MoreWelcome to the inaugural edition of the YugaByte DB Community and Engineering update series! Let’s dive in and take a look at what has happened over the last few weeks.
There has been a lot of activity in terms of meetups and events. In June, YugaByte was at DockerCon. We also did a hands-on lab about building geo-distributed cloud apps at a Datariders meetup and a talk at Samsung about building modern apps at cloud scale.
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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 Amazon DynamoDB and Apache Cassandra initially focused on “big data” use cases that did not require such guarantees and hence avoided implementing them altogether. However, ACID transactions are making a strong comeback in the last 2 years with the launch of next-generation distributed databases that have built-in support for them.
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Read MoreDynamoDB is AWS’s NoSQL alternative to Cassandra, primarily marketed to mid-sized and large enterprises. The uses cases best suited for DynamoDB include those that require a flexible data model, reliable performance, and the automatic scaling of throughput capacity. DynamoDB’s landing page points out that mobile, web, gaming, ad tech, and IoT are all good application types for DynamoDB.
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Read MoreDynamoDB is a fully managed NoSQL database offered by Amazon Web Services. While it works great for smaller scale applications, the limitations it poses in the context of larger scale applications are not well understood. This post aims to help developers and operations engineers understand the precise strengths and weaknesses of DynamoDB, especially when it powers a complex large-scale application.
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