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DBMS > Apache Pinot vs. ToroDB vs. Vertica vs. VictoriaMetrics

System Properties Comparison Apache Pinot vs. ToroDB vs. Vertica vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonToroDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA MongoDB-compatible JSON document store, built on top of PostgreSQLCloud 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.A fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSDocument storeRelational DBMS infoColumn orientedTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitepinot.apache.orggithub.com/­torodb/­serverwww.vertica.comvictoriametrics.com
Technical documentationdocs.pinot.apache.orgvertica.com/­documentationdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software Foundation and contributors8KdataOpenText infopreviously Micro Focus and Hewlett PackardVictoriaMetrics
Initial release2015201620052018
Current release1.0.0, September 202312.0.3, January 2023v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL-V3commercial infoLimited community edition freeOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono 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 languageJavaJavaC++Go
Server operating systemsAll OS with a Java JDK11 or higherAll OS with a Java 7 VMLinuxFreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeYes, 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 dateyesyes infostring, integer, double, boolean, date, object_idyes
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.nonono
Secondary indexesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsJDBCADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesGo
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersnoyes, called Custom Alertsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Synchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache PinotToroDBVertica infoOpenText™ Vertica™VictoriaMetrics
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...
» more
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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More resources
Apache PinotToroDBVertica infoOpenText™ Vertica™VictoriaMetrics
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