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DBMS > Kdb vs. SQream DB vs. Vertica

System Properties Comparison Kdb vs. SQream DB vs. Vertica

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Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonSQream DB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHigh performance Time Series DBMSa 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 modelTime Series DBMS
Vector DBMS
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitekx.comsqream.comwww.vertica.com
Technical documentationcode.kx.comdocs.sqream.comvertica.com/­documentation
DeveloperKx Systems, a division of First Derivatives plcSQream TechnologiesOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2000 infokdb was released 2000, kdb+ in 200320172005
Current release3.6, May 20182022.1.6, December 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree 32-bit versioncommercialcommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqC++, CUDA, Haskell, Java, ScalaC++
Server operating systemsLinux
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 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.yesno
Secondary indexesyes infotable attribute 'grouped'noNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query language (q)yesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
.Net
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
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 infowith viewsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal 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 methodsno infosimilar paradigm used for internal processingnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.yesno
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
KdbSQream DBVertica infoOpenText™ Vertica™
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing modelsupon request
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Cost-based models and subscription-based models are both available. One license is...
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More resources
KdbSQream DBVertica infoOpenText™ Vertica™
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