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DBMS > Kinetica vs. LeanXcale vs. TDSQL for MySQL

System Properties Comparison Kinetica vs. LeanXcale vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonLeanXcale  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.28
Rank#286  Overall
#41  Key-value stores
#130  Relational DBMS
Score0.96
Rank#192  Overall
#88  Relational DBMS
Websitewww.kinetica.comwww.leanxcale.comwww.tencentcloud.com/­products/­dcdb
Technical documentationdocs.kinetica.comwww.tencentcloud.com/­document/­product/­1042
DeveloperKineticaLeanXcaleTencent
Initial release201220152013
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++
Server operating systemsLinuxhosted
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes
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 indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infothrough Apache Derbyyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
Java
Scala
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
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 RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelUsers with fine-grained authorization concept

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More resources
KineticaLeanXcaleTDSQL for MySQL
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