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DBMS > GridGain vs. Hawkular Metrics vs. HEAVY.AI vs. KeyDB

System Properties Comparison GridGain vs. Hawkular Metrics vs. HEAVY.AI vs. KeyDB

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelKey-value store
Relational DBMS
Time Series DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Websitewww.gridgain.comwww.hawkular.orggithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.heavy.aidocs.keydb.dev
DeveloperGridGain Systems, Inc.Community supported by Red HatHEAVY.AI, Inc.EQ Alpha Technology Ltd.
Initial release2007201420162019
Current releaseGridGain 8.5.15.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoBSD-3
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.
Implementation languageJava, C++, .NetJavaC++ and CUDAC++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows
LinuxLinux
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.yesnonono
Secondary indexesyesnonoyes infoby using the Redis Search module
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoyesno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP RESTJDBC
ODBC
Thrift
Vega
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Go
Java
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nonoLua
Triggersyes (cache interceptors and events)yes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)selectable replication factor infobased on CassandraMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsnofine grained access rights according to SQL-standardsimple password-based access control and ACL

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More resources
GridGainHawkular MetricsHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KeyDB
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