Couchbase Adds SQL to Nosql with Couchbase Server

REPORT REPRINT

Couchbase adds SQL to NoSQL with Couchbase Server 4.0 MATT ASLETT 7 OCT 2015 Version 4.0 of the Couchbase Server NoSQL document database adds multi-dimensional scalability and global secondary indexes, improved cross-datacenter replication, and general availability of N1QL, Couchbase’s SQL-based query language.

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Couchbase has launched a major update to its Couchbase Server NoSQL document database. Ver- sion 4.0 adds multi-dimensional scalability and global secondary indexes, improved cross-datacenter replication, and general availability of N1QL (pronounced ‘nickel’), Couchbase’s SQL-based query language.

THE 451 TAKE There is no doubt that Couchbase Server version 4.0 is a substantial release, containing enough enhancements that they could justifiably be spread across multiple point releases. The scale of the update is symptomatic of Couchbase’s ambitions as it looks to increase its competition with the database giants for the next generation of enterprise applications. Capabilities such as a SQL-like query language and secondary indexing will go some way toward improving Couchbase’s chances of be- coming a genuine option for later-stage adopters, as well as the early adopters that have driven the growth of NoSQL to date.

CONTEXT We have previously noted that, while the term NoSQL served to focus attention on the new breed of nonrelational database technologies, including key/value store, document stores and graph databases, SQL itself was not the problem being avoided. Indeed, a better term might be ‘NoSchema,’ given that a more common quality is a rejection of fixed-table schema and join operations. SQL remains a flexible and widely adopted query language, to the extent that many of the NoSQL database vendors have looked to adopt it, or at least mimic it, to bring its benefits to their nonrelational databases. Couch- base is arguably at the forefront of this, and, with the announcement of Couchbase Server 4.0, has delivered the general availability of N1QL, an SQL-based query language for Couchbase Server. NOSQL? NO: SQL N1QL has been in development for several years – a developer preview was made available in 2014 – and es- sentially extends a subset of the SQL relational algebra for the JSON document model, including support for re- cursive objects. The company believes that customers using N1QL will benefit from more efficient development thanks to existing familiarity with the declarative query language and a reduction in the amount of code that needs to be executed within the application. Couchbase Server 4.0 includes an SDK with embedded N1QL cli- ents. The company has also teamed up with data-connectivity specialist Simba to create ODBC and JDBC drivers that will enable integration with business intelligence, data visualization and data management tools designed to operate with SQL databases – such as Microsoft Excel, Tableau, Informatica and Metanautix. SECONDARY INDEXING AND BEYOND Couchbase Server 4.0 adds a number of other new capabilities designed to elevate the database for more strate- gic adoption and mission-critical applications, including global secondary indexing and multi-dimensional scalability. The former is enabled by the latter, which was previewed earlier this year, and enables users to partition nodes in a cluster; designate them for data, index and query workloads; and scale them independently. Rather than have data, index and query workloads compete for resources on all eight nodes in an eight-node cluster, for example, with multi-dimensional scaling, users could designate four nodes to data, and two nodes each to index and query, scaling them independently as required. Global secondary indexing takes advantage of this ability to separate and scale indexing resources separately, improving performance by focusing queries on the two nodes used for index workloads (to continue the example), rather than all eight. Secondary indexing is also enabled by the introduction of a new storage engine in Couchbase Server 4.0. ForestDB is an append-only storage engine optimized for use on solid-state disks that takes advantage of hierarchical B+ tree tries to reduce the height of storage trees and improve performance. While ForestDB will eventually become the default storage engine for Couchbase Server, it is initially being de- ployed specifically to improve the performance of secondary indexes. 451 RESEARCH REPRINT

ADDITIONAL CAPABILITIES While the introduction of an SQL-like query language, global secondary indexing, multi-dimensional scaling and a new storage engine would justifiably be enough for a new release, Couchbase didn’t stop there. Couchbase Server 4.0 also includes security improvements – LDAP integration for authentication and auditing – and improved cross-datacenter replication thanks to the addition of filtering to enable subsets of data to be geographi- cally replicated as required. Also new is support for geospatial queries thanks to multi-dimensional indexes, bloom filters for latency improvements, memory defrag to improve the efficiency of memory utilization, and a ‘breakpad’ for new readable crash and diagnostic logs. Couchbase now counts more than 500 customers for Couchbase Server – including the likes of General Electric, Gannett, Marriott International, Cox Automotive, DIRECTV and Nielsen – up from the ‘more than 450’ cited in March. The company has also grown its headcount to 300, compared with ‘more than 250’ in March. Couchbase has raised $115m in five rounds of funding, with the most recent $60m series E round announced in June 2014. COMPETITION The most direct competition for Couchbase comes from other NoSQL database vendors, including MongoDB, DataStax, Basho, Aerospike, Redis Labs, MarkLogic, and IBM’s Cloudant and Compose, as well as Amazon Web Services’ DynamoDB, Microsoft’s Azure DocumentDB and Google’s Cloud Bigtable. Couchbase sees its closest competitors as MongoDB (for JSON document model use cases) and DataStax (for cross-datacenter scalability), and maintains that it offers advantages over MongoDB in terms of SQL support and DataStax in terms of JSON support. Wider competition comes from the incumbent relational database vendors, including Oracle, IBM, Microsoft and SAP, which continue to dominate the market for operational databases. IBM and Oracle have already added the ability to store JSON documents to their relational databases, and Microsoft is in the process of doing so. All three are likely to argue that the combination will be ‘good enough’ for most mainstream users, although Couchbase and other NoSQL specialists can point to scalability, performance and agility advantages, and argue that simply storing JSON in a relational database is nowhere near good enough for the next-generation applications being developed to take advantage of distributed elastic architecture.

SWOT ANALYSIS

STRENGTHS WEAKNESSES Couchbase Server 4.0 is a substantial re- The company remains behind some rivals lease with a number of key improvements – notably MongoDB – in terms of developer that are likely to appeal to later adopters as traction and mindshare, although less so in they begin to look at potential NoSQL use terms of adoption by paying customers. cases.

OPPORTUNITIES THREATS As more companies begin to consider the The incumbent relational database giants – potential architecture for their next-genera- notably Oracle and IBM, and soon Microsoft tion data platforms, SQL support, secondary – have added support for storing JSON doc- indexing and multi-dimensional scalability uments. Expect them to argue that JSON could be key features. support in the relational database is ‘good enough’ for mainstream users.