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DBMS > Apache IoTDB vs. EJDB vs. GridGain vs. HBase

System Properties Comparison Apache IoTDB vs. EJDB vs. GridGain vs. HBase

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEJDB  Xexclude from comparisonGridGain  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkEmbeddable document-store database library with JSON representation of queries (in MongoDB style)GridGain is an in-memory computing platform, built on Apache IgniteWide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelTime Series DBMSDocument storeKey-value store
Relational DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websiteiotdb.apache.orggithub.com/­Softmotions/­ejdbwww.gridgain.comhbase.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdwww.gridgain.com/­docs/­index.htmlhbase.apache.org/­book.html
DeveloperApache Software FoundationSoftmotionsGridGain Systems, Inc.Apache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2018201220072008
Current release1.1.0, April 2023GridGain 8.5.12.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2commercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJava, C++, .NetJava
Server operating systemsAll OS with a Java VM (>= 1.8)server-lessLinux
OS X
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
Data schemeyesschema-freeyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesoptions to bring your own types, AVRO
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.noyesno
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like query languagenoANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
Native API
in-process shared libraryHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresyesnoyes (compute grid and cache interceptors can be used instead)yes infoCoprocessors in Java
Triggersyesnoyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyes (replicated cache)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes (compute grid and hadoop accelerator)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDSingle row ACID (across millions of columns)
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
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 controlyesnoSecurity Hooks for custom implementationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
Apache IoTDBEJDBGridGainHBase
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