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DBMS > PouchDB vs. SingleStore vs. Sphinx vs. Splice Machine

System Properties Comparison PouchDB vs. SingleStore vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NamePouchDB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionJavaScript DBMS with an API inspired by CouchDBMySQL 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 typeOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.18
Rank#114  Overall
#21  Document stores
Score4.02
Rank#74  Overall
#39  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitepouchdb.comwww.singlestore.comsphinxsearch.comsplicemachine.com
Technical documentationpouchdb.com/­guidesdocs.singlestore.comsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperApache Software FoundationSingleStore Inc.Sphinx Technologies Inc.Splice Machine
Initial release2012201320012014
Current release7.1.1, June 20198.5, January 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Sourcecommercial infofree developer edition availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC++, GoC++Java
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Linux info64 bit version requiredFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyes infovia viewsyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infobut no triggers and foreign keysSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP REST infoonly for PouchDB Server
JavaScript API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesJavaScriptBash
C
C#
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresView functions in JavaScriptyesnoyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infowith a proxy-based framework, named couchdb-loungeSharding infohash partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Source-replica replication infostores two copies of each physical data partition on two separate nodesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infocan define user-defined aggregate functions for map-reduce-style calculationsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infoby using IndexedDB, WebSQL or LevelDB as backendyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlnoFine grained access control via users, groups and rolesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
PouchDBSingleStore infoformer name was MemSQLSphinxSplice Machine
DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
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