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DBMS > chDB vs. Kinetica vs. SQream DB vs. Vertica

System Properties Comparison chDB vs. Kinetica vs. SQream DB vs. Vertica

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Editorial information provided by DB-Engines
NamechDB  Xexclude from comparisonKinetica  Xexclude from comparisonSQream DB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn embedded SQL OLAP Engine powered by ClickHouseFully vectorized database across both GPUs and CPUsa GPU-based, columnar RDBMS for big data analytics workloadsCloud 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 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
Score0.07
Rank#376  Overall
#158  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­chdb-io/­chdbwww.kinetica.comsqream.comwww.vertica.com
Technical documentationdoc.chdb.iodocs.kinetica.comdocs.sqream.comvertica.com/­documentation
DeveloperKineticaSQream TechnologiesOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2023201220172005
Current release7.1, August 20212022.1.6, December 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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.
Implementation languageC, C++C++, CUDA, Haskell, Java, ScalaC++
Server operating systemsserver-lessLinuxLinuxLinux
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 dateyesyes, ANSI Standard SQL Typesyes
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 indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLClose to ANSI SQL (SQL/JSON + extensions)SQL-like DML and DDL statementsyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.Net
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesBun
C
C++
Go
JavaScript (Node.js)
Python
Rust
C++
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsuser defined functions in Pythonyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes 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 nodesShardinghorizontal and vertical partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
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 persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
chDBKineticaSQream DBVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
chDBKineticaSQream DBVertica infoOpenText™ Vertica™
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