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DBMS > Apache IoTDB vs. Datomic vs. GridGain vs. SAP SQL Anywhere vs. Teradata Aster

System Properties Comparison Apache IoTDB vs. Datomic vs. GridGain vs. SAP SQL Anywhere vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatomic  Xexclude from comparisonGridGain  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be 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 FlinkDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGridGain is an in-memory computing platform, built on Apache IgniteRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsPlatform for big data analytics on multistructured data sources and types
Primary database modelTime Series DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score3.95
Rank#80  Overall
#42  Relational DBMS
Websiteiotdb.apache.orgwww.datomic.comwww.gridgain.comwww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.datomic.comwww.gridgain.com/­docs/­index.htmlhelp.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperApache Software FoundationCognitectGridGain Systems, Inc.SAP infoformerly SybaseTeradata
Initial release20182012200719922005
Current release1.1.0, April 20231.0.6735, June 2023GridGain 8.5.117, July 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freecommercialcommercialcommercial
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 languageJavaJava, ClojureJava, C++, .Net
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyesyesyes infoin Aster File Store
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoANSI-99 for query and DML statements, subset of DDLyesyes
APIs and other access methodsJDBC
Native API
RESTful HTTP APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Clojure
Java
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsyes (compute grid and cache interceptors can be used instead)yes, in C/C++, Java, .Net or PerlR packages
TriggersyesBy using transaction functionsyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)none infoBut extensive use of caching in the application peersShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoBut extensive use of caching in the application peersyes (replicated cache)Source-replica replication infoDatabase mirroringyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes (compute grid and hadoop accelerator)noyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesyesno
User concepts infoAccess controlyesnoSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBDatomicGridGainSAP SQL Anywhere infoformerly called Adaptive Server AnywhereTeradata Aster
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