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DBMS > Elasticsearch vs. EsgynDB vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. Splice Machine

System Properties Comparison Elasticsearch vs. EsgynDB vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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 metricEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen 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 DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.78
Rank#7  Overall
#1  Search engines
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitewww.elastic.co/­elasticsearchwww.esgyn.cnazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comsplicemachine.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperElasticEsgynMicrosoftSphinx Technologies Inc.Splice Machine
Initial release20102015201620012014
Current release8.6, January 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaC++C++Java
Server operating systemsAll OS with a Java VMLinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonono
Secondary indexesyes infoAll search fields are automatically indexedyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageyesyesSQL-like query language (SphinxQL)yes
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
Java
PHP
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 proceduresyesJava Stored ProceduresTransact SQLnoyes infoJava
Triggersyes infoby using the 'percolation' featurenononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal 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 nodesyesMulti-source replication between multi datacentersyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectoryesnonoYes, 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, allImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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 integrationnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
ElasticsearchEsgynDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxSplice Machine
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