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DBMS > GridGain vs. HEAVY.AI vs. OpenTSDB

System Properties Comparison GridGain vs. HEAVY.AI vs. OpenTSDB

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonOpenTSDB  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareScalable Time Series DBMS based on HBase
Primary database modelKey-value store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score1.73
Rank#147  Overall
#12  Time Series DBMS
Websitewww.gridgain.comgithub.com/­heavyai/­heavydb
www.heavy.ai
opentsdb.net
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.heavy.aiopentsdb.net/­docs/­build/­html/­index.html
DeveloperGridGain Systems, Inc.HEAVY.AI, Inc.currently maintained by Yahoo and other contributors
Initial release200720162011
Current releaseGridGain 8.5.15.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoLGPL
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++ and CUDAJava
Server operating systemsLinux
OS X
Solaris
Windows
LinuxLinux
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnumeric data for metrics, strings for tags
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.yesnono
Secondary indexesyesnono
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyesno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Vega
HTTP API
Telnet API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
Erlang
Go
Java
Python
R
Ruby
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nono
Triggersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Multi-source replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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.yesyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardno

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More resources
GridGainHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022OpenTSDB
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