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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFatDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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 .NET NoSQL DBMS that can integrate with and extend SQL Server.A 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 modelTime Series DBMSDocument store
Key-value store
Graph DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Websiteiotdb.apache.orgwww.graphengine.ioazure.microsoft.com/­services/­synapse-analytics
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.microsoft.com/­azure/­synapse-analytics
DeveloperApache Software FoundationFatCloudMicrosoftMicrosoft
Initial release2018201220102016
Current release1.1.0, April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#.NET and CC++
Server operating systemsAll OS with a Java VM (>= 1.8)Windows.NEThosted
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL Servernoyes
APIs and other access methodsJDBC
Native API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#C#
C++
F#
Visual Basic
C#
Java
PHP
Server-side scripts infoStored proceduresyesyes infovia applicationsyesTransact SQL
Triggersyesyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioningSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono 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 datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: 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.yesyes
User concepts infoAccess controlyesno infoCan implement custom security layer via applicationsyes

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More resources
Apache IoTDBFatDBGraph Engine infoformer name: TrinityMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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