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DBMS > Datomic vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. TimescaleDB

System Properties Comparison Datomic vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityElastic, 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 modelRelational DBMSRelational DBMSSearch engineTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  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.datomic.comazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comwww.timescale.com
Technical documentationdocs.datomic.comdocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docsdocs.timescale.com
DeveloperCognitectMicrosoftSphinx Technologies Inc.Timescale
Initial release2012201620012017
Current release1.0.6735, June 20233.5.1, February 20232.13.0, November 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++C++C
Server operating systemsAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesnonumerics, 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.nonoyes
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyesSQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
Proprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
Java
C#
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 proceduresyes infoTransaction FunctionsTransact SQLnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersBy using transaction functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding, 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 nodesnone infoBut extensive use of caching in the application peersyesnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono 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 dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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.yes inforecommended only for testing and developmentno
User concepts infoAccess controlnoyesnofine grained access rights according to SQL-standard

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