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DBMS > Badger vs. GridDB vs. HEAVY.AI vs. Ignite vs. LevelDB

System Properties Comparison Badger vs. GridDB vs. HEAVY.AI vs. Ignite vs. LevelDB

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGridDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIgnite  Xexclude from comparisonLevelDB  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Scalable in-memory time series database optimized for IoT and Big DataA 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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelKey-value storeTime Series DBMSRelational DBMSKey-value store
Relational DBMS
Key-value store
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Websitegithub.com/­dgraph-io/­badgergriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
ignite.apache.orggithub.com/­google/­leveldb
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.griddb.netdocs.heavy.aiapacheignite.readme.io/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDGraph LabsToshiba CorporationHEAVY.AI, Inc.Apache Software FoundationGoogle
Initial release20172013201620152011
Current release5.1, August 20225.10, January 2022Apache Ignite 2.61.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open 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 languageGoC++C++ and CUDAC++, Java, .NetC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinuxLinux
OS X
Solaris
Windows
Illumos
Linux
OS X
Windows
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesyesno
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.nononoyesno
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesGoC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresnononoyes (compute grid and cache interceptors can be used instead)no
Triggersnoyesnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replicationyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnoACIDno
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.noyesyesyes
User concepts infoAccess controlnoAccess rights for users can be defined per databasefine grained access rights according to SQL-standardSecurity Hooks for custom implementationsno
More information provided by the system vendor
BadgerGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IgniteLevelDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
BadgerGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IgniteLevelDB
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