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DBMS > Graphite vs. GridDB vs. HBase vs. Ignite

System Properties Comparison Graphite vs. GridDB vs. HBase vs. Ignite

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Editorial information provided by DB-Engines
NameGraphite  Xexclude from comparisonGridDB  Xexclude from comparisonHBase  Xexclude from comparisonIgnite  Xexclude from comparison
DescriptionData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperScalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTableApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelTime Series DBMSTime Series DBMSWide column storeKey-value store
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.75
Rank#75  Overall
#5  Time Series DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Websitegithub.com/­graphite-project/­graphite-webgriddb.nethbase.apache.orgignite.apache.org
Technical documentationgraphite.readthedocs.iodocs.griddb.nethbase.apache.org/­book.htmlapacheignite.readme.io/­docs
DeveloperChris DavisToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release2006201320082015
Current release5.1, August 20222.3.4, January 2021Apache Ignite 2.6
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 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languagePythonC++JavaC++, Java, .Net
Server operating systemsLinux
Unix
LinuxLinux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateNumeric data onlyyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyes
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.nononoyes
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)noANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsHTTP API
Sockets
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesJavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes (compute grid and cache interceptors can be used instead)
Triggersnoyesyesyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
Source-replica replication
yes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayes infolockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlnoAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACSecurity Hooks for custom implementations
More information provided by the system vendor
GraphiteGridDBHBaseIgnite
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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GraphiteGridDBHBaseIgnite
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