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DBMS > AnzoGraph DB vs. HEAVY.AI vs. Kinetica vs. LeanXcale vs. LevelDB

System Properties Comparison AnzoGraph DB vs. HEAVY.AI vs. Kinetica vs. LeanXcale vs. LevelDB

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonLeanXcale  Xexclude from comparisonLevelDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSKey-value store
Relational DBMS
Key-value store
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Websitecambridgesemantics.com/­anzographgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comwww.leanxcale.comgithub.com/­google/­leveldb
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.heavy.aidocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperCambridge SemanticsHEAVY.AI, Inc.KineticaLeanXcaleGoogle
Initial release20182016201220152011
Current release2.3, January 20215.10, January 20227.1, August 20211.23, February 2021
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC, C++C++
Server operating systemsLinuxLinuxLinuxIllumos
Linux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesnonoyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yesSQL-like DML and DDL statementsyes infothrough Apache Derbyno
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languagesC++
Java
Python
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C
Java
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functionsno
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoRound robinShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess rights for users and roles on table levelno

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More resources
AnzoGraph DBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaLeanXcaleLevelDB
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