DBMS > Couchbase vs. Oracle vs. SingleStore vs. Splice Machine vs. TimesTen
System Properties Comparison Couchbase vs. Oracle vs. SingleStore vs. Splice Machine vs. TimesTen
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Name | Couchbase Originally called Membase Xexclude from comparison | Oracle Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | Splice Machine Xexclude from comparison | TimesTen Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | Widely used RDBMS | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark | An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store | Relational DBMS | Relational DBMS | Relational DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Key-value store originating from the former Membase product and supporting the Memcached protocol Spatial DBMS using the Geocouch extension Search engine Time Series DBMS Vector DBMS | Document store Graph DBMS with Oracle Spatial and Graph RDF store with Oracle Spatial and Graph Spatial DBMS with Oracle Spatial and Graph Vector DBMS since Oracle 23 | Document store Spatial DBMS Time Series DBMS Vector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.couchbase.com | www.oracle.com/database | www.singlestore.com | splicemachine.com | www.oracle.com/database/technologies/related/timesten.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.couchbase.com | docs.oracle.com/en/database | docs.singlestore.com | splicemachine.com/how-it-works | docs.oracle.com/en/database/other-databases/timesten/index.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Couchbase, Inc. | Oracle | SingleStore Inc. | Splice Machine | Oracle originally founded in HP Labs it was acquired by Oracle in 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2011 | 1980 | 2013 | 2014 | 1998 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 23c, September 2023 | 8.5, January 2024 | 3.1, March 2021 | Release 22.1 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Business Source License (BSL 1.1); Commercial licenses also available | commercial restricted free version is available | commercial free developer edition available | Open Source AGPL 3.0, commercial license available | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C, C++, Go and Erlang | C and C++ | C++, Go | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | AIX HP-UX Linux OS X Solaris Windows z/OS | Linux 64 bit version required | Linux OS X Solaris Windows | IBM AIX Power PC 64-bit Linux arm64 Linux x86-64 Solaris SPARC 64 Solaris SPARC/x86 Solaris x86-64 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes Schemaless in JSON and XML columns | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes with proprietary extensions | yes but no triggers and foreign keys | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | JDBC ODBC ODP.NET Oracle Call Interface (OCI) | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | JDBC Native Spark Datasource ODBC | ODBC ODP.NET Oracle Call Interface (OCI) Pro*C/C++ programming interfaces SQL and PL/SQL via JDBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C Go Java JavaScript Node.js Kotlin PHP Python Ruby Scala | C C# C++ Clojure Cobol Delphi Eiffel Erlang Fortran Groovy Haskell Java JavaScript Lisp Objective C OCaml Perl PHP Python R Ruby Scala Tcl Visual Basic | Bash C C# Java JavaScript (Node.js) Python | C# C++ Java JavaScript (Node.js) Python R Scala | C C++ Java Node.js PL/SQL Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | PL/SQL also stored procedures in Java possible | yes | yes Java | PL/SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes via the TAP protocol | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Automatic Sharding | Sharding, horizontal partitioning | Sharding hash partitioning | Shared Nothhing Auto-Sharding, Columnar Partitioning | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication including cross data center replication Source-replica replication | Multi-source replication Source-replica replication | Source-replica replication stores two copies of each physical data partition on two separate nodes | Multi-source replication Source-replica replication | Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | no can be realized in PL/SQL | no can define user-defined aggregate functions for map-reduce-style calculations | Yes, via Full Spark Integration | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency or Eventual Consistency depending on configuration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID isolation level can be parameterized | ACID | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes, multi-version concurrency control (MVCC) | yes, multi-version concurrency control (MVCC) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | yes | yes by means of logfiles and checkpoints | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes Ephemeral buckets | yes Version 12c introduced the new option 'Oracle Database In-Memory' | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | fine grained access rights according to SQL-standard | Fine grained access control via users, groups and roles | Access rights for users, groups and roles according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Couchbase Originally called Membase | Oracle | SingleStore former name was MemSQL | Splice Machine | TimesTen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | MySQL is the DBMS of the Year 2019 The struggle for the hegemony in Oracle's database empire Architecting eCommerce Platforms for Zero Downtime on Black Friday and Beyond | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Edward Anderson Spends US$298k Buying Couchbase Shares EVR Research LP Acquires 179,585 Shares of Couchbase, Inc. (NASDAQ:BASE) Couchbase’s stock crumbles on anticipation of significant growth slowdown Couchbase director Anderson buys $298k in company stock Couchbase reports 20% Q2 revenue growth, though analysts expected more provided by Google News | OCI Full Stack DR adds even more database and storage capabilities Microsoft and Oracle enhance Oracle Database@Azure with data and AI integration AWS Weekly Roundup: Oracle Database@AWS, Amazon RDS, AWS PrivateLink, Amazon MSK, Amazon EventBridge, Amazon SageMaker and more | Amazon Web Services Oracle inks deal with AWS to offer database services Oracle Stock: Analyst Sees Microsoft, AWS, Google Deals Unlocking Growth provided by Google News | SingleStore Partners With Snowflake to Help Users Build Faster, More Efficient Real Time AI Applications SingleStore CEO sees little future for purpose-built vector databases Achieve near real-time analytics on Amazon DynamoDB with SingleStore Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore: We do vectors and you don’t need knowledge graphs provided by Google News | Machine learning data pipeline outfit Splice Machine files for insolvency Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning Monte Zweben's Splice Machine Introduces New Hadoop RDBMS Splice Machine Launches Feature Store to Simplify Feature Engineering Hadoop is not a static data repository, says Splice Machine CEO | #BigDataSV provided by Google News | Oracle starts peddling Exalytics in-memory appliance The Intel Xeon E7-8800 v3 Review: The POWER8 Killer? provided by Google News |
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