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DBMS > Sphinx vs. TimesTen vs. Vertica

System Properties Comparison Sphinx vs. TimesTen vs. Vertica

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Editorial information provided by DB-Engines
NameSphinx  Xexclude from comparisonTimesTen  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen source search engine for searching in data from different sources, e.g. relational databasesIn-Memory RDBMS compatible to OracleCloud 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.
Primary database modelSearch engineRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.03
Rank#60  Overall
#6  Search engines
Score1.35
Rank#165  Overall
#75  Relational DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitesphinxsearch.comwww.oracle.com/­database/­technologies/­related/­timesten.htmlwww.vertica.com
Technical documentationsphinxsearch.com/­docsdocs.oracle.com/­database/­timesten-18.1vertica.com/­documentation
DeveloperSphinx Technologies Inc.Oracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005OpenText infopreviously Micro Focus and Hewlett Packard
Initial release200119982005
Current release3.5.1, February 202311 Release 2 (11.2.2.8.0)12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoGPL version 2, commercial licence availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenoyesyes
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.nono
Secondary indexesyes infofull-text index on all search fieldsyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query language (SphinxQL)yesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsProprietary protocolJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C++
Java
PL/SQL
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoPL/SQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportednonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoThe original contents of fields are not stored in the Sphinx index.yes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
SphinxTimesTenVertica infoOpenText™ Vertica™
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...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
SphinxTimesTenVertica infoOpenText™ Vertica™
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