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DBMS > Sphinx vs. TerminusDB vs. Vertica

System Properties Comparison Sphinx vs. TerminusDB vs. Vertica

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Editorial information provided by DB-Engines
NameSphinx  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen source search engine for searching in data from different sources, e.g. relational databasesScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationshipsCloud 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 engineGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
RDF store
Spatial 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
Score0.22
Rank#323  Overall
#28  Graph DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitesphinxsearch.comterminusdb.comwww.vertica.com
Technical documentationsphinxsearch.com/­docsterminusdb.github.io/­terminusdb/­#vertica.com/­documentation
DeveloperSphinx Technologies Inc.DataChemist Ltd.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release200120182005
Current release3.5.1, February 202311.0.0, January 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3commercial 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++Prolog, RustC++
Server operating systemsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
LinuxLinux
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 fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query language (SphinxQL)SQL-like query language (WOQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsProprietary protocolOWL
RESTful HTTP API
WOQL (Web Object Query Language)
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
JavaScript
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportedGraph Partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneJournaling StreamsMulti-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
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 infoin-memory journalingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlnoRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
SphinxTerminusDB infoformer name was DataChemistVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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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SphinxTerminusDB infoformer name was DataChemistVertica infoOpenText™ Vertica™
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