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DBMS > Apache Pinot vs. ClickHouse vs. Kinetica vs. SiriDB vs. Vertica

System Properties Comparison Apache Pinot vs. ClickHouse vs. Kinetica vs. SiriDB vs. Vertica

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonClickHouse  Xexclude from comparisonKinetica  Xexclude from comparisonSiriDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.Fully vectorized database across both GPUs and CPUsOpen Source Time Series DBMSCloud 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 modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score16.34
Rank#38  Overall
#23  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitepinot.apache.orgclickhouse.comwww.kinetica.comsiridb.comwww.vertica.com
Technical documentationdocs.pinot.apache.orgclickhouse.com/­docsdocs.kinetica.comdocs.siridb.comvertica.com/­documentation
DeveloperApache Software Foundation and contributorsClickhouse Inc.KineticaCesbitOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20152016201220172005
Current release1.0.0, September 2023v24.4.1.2088-stable, May 20247.1, August 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source infoMIT Licensecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
  • ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
Implementation languageJavaC++C, C++CC++
Server operating systemsAll OS with a Java JDK11 or higherFreeBSD
Linux
macOS
LinuxLinuxLinux
Data schemeyesyesyesyesYes, 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 dateyesyesyesyes infoNumeric datayes
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.nononono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageClose to ANSI SQL (SQL/JSON + extensions)SQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCgRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
JDBC
ODBC
RESTful HTTP API
HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
Python
C# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Rust
Scala info3rd party library
C++
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningkey based and customShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.Source-replica replicationyesMulti-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 methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.Access rights for users and roles on table levelsimple rights management via user accountsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache PinotClickHouseKineticaSiriDBVertica 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...
» 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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesAiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
» more

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache PinotClickHouseKineticaSiriDBVertica infoOpenText™ Vertica™
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