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DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. GridGain vs. Tkrzw vs. Yaacomo

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. GridGain vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGridGain  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYaacomo  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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 FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksGridGain is an in-memory computing platform, built on Apache IgniteA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelTime Series DBMSDocument store
Key-value store
Key-value store
Relational DBMS
Key-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score0.09
Rank#354  Overall
#51  Key-value stores
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gridgain.comdbmx.net/­tkrzwyaacomo.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.html
DeveloperApache Software FoundationAtos Convergence CreatorsGridGain Systems, Inc.Mikio HirabayashiQ2WEB GmbH
Initial release20182016200720202009
Current release1.1.0, April 20231703GridGain 8.5.10.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2.0commercial
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 languageJavaJavaJava, C++, .NetC++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Solaris
Windows
Linux
macOS
Android
Linux
Windows
Data schemeyesSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateyesoptionalyesnoyes
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.noyesyesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoANSI-99 for query and DML statements, subset of DDLnoyes
APIs and other access methodsJDBC
Native API
LDAPHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesnoyes (compute grid and cache interceptors can be used instead)no
Triggersyesyesyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes (replicated cache)noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infousing specific database classesyes
User concepts infoAccess controlyesLDAP bind authenticationSecurity Hooks for custom implementationsnofine grained access rights according to SQL-standard

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More resources
Apache IoTDBAtos Standard Common RepositoryGridGainTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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