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DBMS > Elasticsearch vs. EsgynDB vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. TimescaleDB

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

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 comparisonTimescaleDB  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 databasesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelSearch engineRelational DBMSRelational DBMSSearch engineTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Relational 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
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websitewww.elastic.co/­elasticsearchwww.esgyn.cnazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comwww.timescale.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docsdocs.timescale.com
DeveloperElasticEsgynMicrosoftSphinx Technologies Inc.Timescale
Initial release20102015201620012017
Current release8.6, January 20233.5.1, February 20232.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
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++C
Server operating systemsAll OS with a Java VMLinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
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 infofull PostgreSQL SQL syntax
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesJava Stored ProceduresTransact SQLnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
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 supportedyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyesnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryesnonono
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
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 integrationnono
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnofine grained access rights according to SQL-standard

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More resources
ElasticsearchEsgynDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxTimescaleDB
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