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DBMS > Elasticsearch vs. PlanetScale vs. Sphinx vs. Splice Machine

System Properties Comparison Elasticsearch vs. PlanetScale vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonPlanetScale  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricScalable, distributed, serverless MySQL database platform built on top of VitessOpen 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 modelSearch engineRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.elastic.co/­elasticsearchplanetscale.comsphinxsearch.comsplicemachine.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlplanetscale.com/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperElasticPlanetScaleSphinx Technologies Inc.Splice Machine
Initial release2010202020012014
Current release8.6, January 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++Java
Server operating systemsAll OS with a Java VMDocker
Linux
macOS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.no
Secondary indexesyes infoAll search fields are automatically indexedyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsSQL-like query language (SphinxQL)yes
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
MySQL protocol
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
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 proceduresyesyes infoproprietary syntaxnoyes infoJava
Triggersyes infoby using the 'percolation' featureyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding 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 nodesyesMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectornonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integritynoyes infonot for MyISAM storage enginenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at shard levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes 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.Memcached and Redis integrationyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept infono user groups or rolesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
ElasticsearchPlanetScaleSphinxSplice Machine
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