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DBMS > GridGain vs. Heroic vs. LevelDB vs. SQream DB

System Properties Comparison GridGain vs. Heroic vs. LevelDB vs. SQream DB

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHeroic  Xexclude from comparisonLevelDB  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesa GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelKey-value store
Relational DBMS
Time Series DBMSKey-value storeRelational 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
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitewww.gridgain.comgithub.com/­spotify/­heroicgithub.com/­google/­leveldbsqream.com
Technical documentationwww.gridgain.com/­docs/­index.htmlspotify.github.io/­heroicgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.sqream.com
DeveloperGridGain Systems, Inc.SpotifyGoogleSQream Technologies
Initial release2007201420112017
Current releaseGridGain 8.5.11.23, February 20212022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaC++C++, CUDA, Haskell, Java, Scala
Server operating systemsLinux
OS X
Solaris
Windows
Illumos
Linux
OS X
Windows
Linux
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes, ANSI Standard SQL Types
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 indexesyesyes infovia Elasticsearchnono
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnonoyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HQL (Heroic Query Language, a JSON-based language)
HTTP API
.Net
JDBC
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nonouser defined functions in Python
Triggersyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesnonenone
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
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlSecurity Hooks for custom implementationsno

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GridGainHeroicLevelDBSQream DB
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