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DBMS > Adabas vs. Apache Druid vs. Apache IoTDB vs. Graph Engine vs. Microsoft Azure Synapse Analytics

System Properties Comparison Adabas vs. Apache Druid vs. Apache IoTDB vs. Graph Engine vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn 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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelMultivalue DBMSRelational DBMS
Time Series DBMS
Time Series DBMSGraph DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.17
Rank#94  Overall
#1  Multivalue DBMS
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmldruid.apache.orgiotdb.apache.orgwww.graphengine.ioazure.microsoft.com/­services/­synapse-analytics
Technical documentationdruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­azure/­synapse-analytics
DeveloperSoftware AGApache Software Foundation and contributorsApache Software FoundationMicrosoftMicrosoft
Initial release19712012201820102016
Current release29.0.1, April 20241.1.0, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava.NET and CC++
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
Linux
OS X
Unix
All OS with a Java VM (>= 1.8).NEThosted
Data schemeyesyes infoschema-less columns are supportedyesyesyes
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.nonononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaySQL for queryingSQL-like query languagenoyes
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
JDBC
RESTful HTTP/JSON API
JDBC
Native API
RESTful HTTP APIADO.NET
JDBC
ODBC
Supported programming languagesNaturalClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
C#
Java
PHP
Server-side scripts infoStored proceduresin NaturalnoyesyesTransact SQL
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event Replicatoryes, via HDFS, S3 or other storage enginesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoIntegration with Hadoop and Sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynonononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesyes

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More resources
Adabas infodenotes "adaptable data base"Apache DruidApache IoTDBGraph Engine infoformer name: TrinityMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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