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DBMS > HEAVY.AI vs. Kinetica vs. LevelDB vs. SingleStore

System Properties Comparison HEAVY.AI vs. Kinetica vs. LevelDB vs. SingleStore

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonLevelDB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score5.60
Rank#62  Overall
#35  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comgithub.com/­google/­leveldbwww.singlestore.com
Technical documentationdocs.heavy.aidocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.singlestore.com
DeveloperHEAVY.AI, Inc.KineticaGoogleSingleStore Inc.
Initial release2016201220112013
Current release5.10, January 20227.1, August 20211.23, February 20218.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoBSDcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageC++ and CUDAC, C++C++C++, Go
Server operating systemsLinuxLinuxIllumos
Linux
OS X
Windows
Linux info64 bit version required
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesnoyesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functionsnoyes
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingnoneSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationnoneSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelnoFine grained access control via users, groups and roles
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaLevelDBSingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaLevelDBSingleStore infoformer name was MemSQL
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SingleStore: The Increasing Momentum of Multi-Model Database Systems
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