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DBMS > Apache IoTDB vs. Ehcache vs. Sadas Engine vs. Teradata Aster vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Ehcache vs. Sadas Engine vs. Teradata Aster vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEhcache  Xexclude from comparisonSadas Engine  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTimescaleDB  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 FlinkA widely adopted Java cache with tiered storage optionsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsPlatform for big data analytics on multistructured data sources and typesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSKey-value storeRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteiotdb.apache.orgwww.ehcache.orgwww.sadasengine.comwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ehcache.org/­documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.timescale.com
DeveloperApache Software FoundationTerracotta Inc, owned by Software AGSADAS s.r.l.TeradataTimescale
Initial release20182009200620052017
Current release1.1.0, April 20233.10.0, March 20228.02.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercial infofree trial version availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMAIX
Linux
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyesyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 infoin Aster File Storeyes
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
JCacheJDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C#
C++
Java
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnonoR packagesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes infoCache Event Listenersnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoby using Terracotta Serverhorizontal partitioningShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoby using Terracotta Servernoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Tunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infosupports JTA and can work as an XA resourceACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBEhcacheSadas EngineTeradata AsterTimescaleDB
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