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DBMS > Kdb vs. STSdb vs. SurrealDB vs. Vertica

System Properties Comparison Kdb vs. STSdb vs. SurrealDB vs. Vertica

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Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonSTSdb  Xexclude from comparisonSurrealDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHigh performance Time Series DBMSKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA fully ACID transactional, developer-friendly, multi-model 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 modelTime Series DBMS
Vector DBMS
Key-value storeDocument store
Graph DBMS
Relational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.03
Rank#365  Overall
#54  Key-value stores
Score1.11
Rank#174  Overall
#30  Document stores
#17  Graph DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitekx.comgithub.com/­STSSoft/­STSdb4surrealdb.comwww.vertica.com
Technical documentationcode.kx.comsurrealdb.com/­docsvertica.com/­documentation
DeveloperKx Systems, a division of First Derivatives plcSTS Soft SCSurrealDB LtdOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2000 infokdb was released 2000, kdb+ in 2003201120222005
Current release3.6, May 20184.0.8, September 2015v1.5.0, May 202412.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree 32-bit versionOpen Source infoGPLv2, commercial license availableOpen Sourcecommercial 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

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Implementation languageqC#RustC++
Server operating systemsLinux
OS X
Solaris
Windows
WindowsLinux
macOS
Windows
Linux
Data schemeyesyesschema-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 infoprimitive types and user defined types (classes)yesyes
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)noSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
.NET Client APIGraphQL
RESTful HTTP API
WebSocket
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
Deno
Go
JavaScript (Node.js)
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infowith viewsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnonehorizontal 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 processingnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.yesno
User concepts infoAccess controlrights management via user accountsnoyes, based on authentication and database rulesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
KdbSTSdbSurrealDBVertica infoOpenText™ Vertica™
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
KdbSTSdbSurrealDBVertica infoOpenText™ Vertica™
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