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DBMS > Sphinx vs. TimescaleDB vs. UniData,UniVerse vs. Vertica vs. Vitess

System Properties Comparison Sphinx vs. TimescaleDB vs. UniData,UniVerse vs. Vertica vs. Vitess

Editorial information provided by DB-Engines
NameSphinx  Xexclude from comparisonTimescaleDB  Xexclude from comparisonUniData,UniVerse  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionOpen 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 PostgreSQLMultiValue database and application server with SQL mapping layer and meta database capabilitiesCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelSearch engineTime Series DBMSMultivalue DBMSRelational DBMS infoColumn orientedRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.95
Rank#55  Overall
#5  Search engines
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score2.85
Rank#98  Overall
#1  Multivalue DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitesphinxsearch.comwww.timescale.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidatawww.vertica.comvitess.io
Technical documentationsphinxsearch.com/­docsdocs.timescale.comdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidatavertica.com/­documentationvitess.io/­docs
DeveloperSphinx Technologies Inc.TimescaleRocket SoftwareOpenText infopreviously Micro Focus and Hewlett PackardThe Linux Foundation, PlanetScale
Initial release20012017198520052013
Current release3.5.1, February 20232.15.0, May 202412.0.3, January 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0commercialcommercial infoLimited community edition freeOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CCC++Go
Server operating systemsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
AIX
HP-UX
Linux
Solaris
Windows
LinuxDocker
Linux
macOS
Data schemeyesyesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
Typing infopredefined data types such as float or datenonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesoptionalyesyes
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.yesno
Secondary indexesyes infofull-text index on all search fieldsyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLSQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntaxyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes infowith proprietary extensions
APIs and other access methodsProprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++ 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
.Net
Basic infoU2 Basic
C
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyesyes, PostgreSQL PL/pgSQL, with minor differencesyes infoproprietary syntax
Triggersnoyesyes infoU2 Basicyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportedyes, across time and space (hash partitioning) attributesnonehorizontal partitioning, hierarchical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication with hot standby and reads on replicas infoSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoconfigurableACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyes infoThe original contents of fields are not stored in the Sphinx index.yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights according to SQL-standard and operating system basedfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
SphinxTimescaleDBUniData,UniVerseVertica infoOpenText™ Vertica™Vitess
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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SphinxTimescaleDBUniData,UniVerseVertica infoOpenText™ Vertica™Vitess
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