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DBMS > Fujitsu Enterprise Postgres vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. TimescaleDB vs. WakandaDB

System Properties Comparison Fujitsu Enterprise Postgres vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. TimescaleDB vs. WakandaDB

Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  Xexclude from comparisonTimescaleDB  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Elastic, 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 PostgreSQLWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSSearch engineTime Series DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.postgresql.fastware.comazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comwww.timescale.comwakanda.github.io
Technical documentationwww.postgresql.fastware.com/­product-manualsdocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docsdocs.timescale.comwakanda.github.io/­doc
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyMicrosoftSphinx Technologies Inc.TimescaleWakanda SAS
Initial release2016200120172012
Current releaseFujitsu Enterprise Postgres 14, January 20223.5.1, February 20232.15.0, May 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C++CC++, JavaScript
Server operating systemsLinux
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.noyesno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesyesSQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntaxno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
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
JavaScript
Server-side scripts infoStored proceduresuser defined functionsTransact SQLnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnoneSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno 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 dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnofine grained access rights according to SQL-standardyes

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More resources
Fujitsu Enterprise PostgresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxTimescaleDBWakandaDB
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