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DBMS > Apache IoTDB vs. GridGain vs. IRONdb vs. Microsoft Azure Synapse Analytics vs. SiteWhere

System Properties Comparison Apache IoTDB vs. GridGain vs. IRONdb vs. Microsoft Azure Synapse Analytics vs. SiteWhere

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGridGain  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSiteWhere  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded 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 FlinkGridGain is an in-memory computing platform, built on Apache IgniteA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerM2M integration platform for persisting/querying time series data
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Time Series DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Websiteiotdb.apache.orgwww.gridgain.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­synapse-analyticsgithub.com/­sitewhere/­sitewhere
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmldocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­azure/­synapse-analyticssitewhere1.sitewhere.io/­index.html
DeveloperApache Software FoundationGridGain Systems, Inc.Circonus LLC.MicrosoftSiteWhere
Initial release20182007201720162010
Current release1.1.0, April 2023GridGain 8.5.1V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetC and C++C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
LinuxhostedLinux
OS X
Windows
Data schemeyesyesschema-freeyespredefined scheme
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesyes
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.noyesnonono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLSQL-like query language (Circonus Analytics Query Language: CAQL)yesno
APIs and other access methodsJDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP APIADO.NET
JDBC
ODBC
HTTP REST
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
Java
PHP
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)yes, in LuaTransact SQL
Triggersyesyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingAutomatic, metric affinity per nodeSharding, horizontal partitioningSharding infobased on HBase
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 (replicated cache)configurable replication factor, datacenter awareyesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
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 datanoACIDnoACIDno
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.yesyesnono
User concepts infoAccess controlyesSecurity Hooks for custom implementationsnoyesUsers with fine-grained authorization concept

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More resources
Apache IoTDBGridGainIRONdbMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSiteWhere
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