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DBMS > Apache Druid vs. Apache IoTDB vs. GridGain vs. Microsoft Azure Synapse Analytics vs. Warp 10

System Properties Comparison Apache Druid vs. Apache IoTDB vs. GridGain vs. Microsoft Azure Synapse Analytics vs. Warp 10

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionOpen-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 FlinkGridGain is an in-memory computing platform, built on Apache IgniteElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSKey-value store
Relational DBMS
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitedruid.apache.orgiotdb.apache.orgwww.gridgain.comazure.microsoft.com/­services/­synapse-analyticswww.warp10.io
Technical documentationdruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­azure/­synapse-analyticswww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation and contributorsApache Software FoundationGridGain Systems, Inc.MicrosoftSenX
Initial release20122018200720162015
Current release29.0.1, April 20241.1.0, April 2023GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava, C++, .NetC++Java
Server operating systemsLinux
OS X
Unix
All OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesyesyesschema-free
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.nonoyesnono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like query languageANSI-99 for query and DML statements, subset of DDLyesno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
PHP
Server-side scripts infoStored proceduresnoyesyes (compute grid and cache interceptors can be used instead)Transact SQLyes infoWarpScript
Triggersnoyesyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding, horizontal partitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes (replicated cache)yesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
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.noyesyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesSecurity Hooks for custom implementationsyesMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache DruidApache IoTDBGridGainMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseWarp 10
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