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DBMS > EsgynDB vs. HEAVY.AI vs. Ignite vs. JanusGraph vs. Kinetica

System Properties Comparison EsgynDB vs. HEAVY.AI vs. Ignite vs. JanusGraph vs. Kinetica

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIgnite  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Fully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Graph DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitewww.esgyn.cngithub.com/­heavyai/­heavydb
www.heavy.ai
ignite.apache.orgjanusgraph.orgwww.kinetica.com
Technical documentationdocs.heavy.aiapacheignite.readme.io/­docsdocs.janusgraph.orgdocs.kinetica.com
DeveloperEsgynHEAVY.AI, Inc.Apache Software FoundationLinux Foundation; originally developed as Titan by AureliusKinetica
Initial release20152016201520172012
Current release5.10, January 2022Apache Ignite 2.60.6.3, February 20237.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC++ and CUDAC++, Java, .NetJavaC, C++
Server operating systemsLinuxLinuxLinux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Linux
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyesnono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyesyesANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
Vega
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetAll languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Clojure
Java
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes (compute grid and cache interceptors can be used instead)yesuser defined functions
Triggersnonoyes (cache interceptors and events)yesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replicationyes (replicated cache)yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes (compute grid and hadoop accelerator)yes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsUser authentification and security via Rexster Graph ServerAccess rights for users and roles on table level

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More resources
EsgynDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IgniteJanusGraph infosuccessor of TitanKinetica
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