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DBMS > Apache IoTDB vs. Dgraph vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Splice Machine

System Properties Comparison Apache IoTDB vs. Dgraph vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Splice Machine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDgraph  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSplice Machine  Xexclude from comparison
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 FlinkDistributed and scalable native Graph DBMSA 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 ServerOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSGraph DBMSGraph DBMS
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteiotdb.apache.orgdgraph.iowww.graphengine.ioazure.microsoft.com/­services/­synapse-analyticssplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldgraph.io/­docswww.graphengine.io/­docs/­manualdocs.microsoft.com/­azure/­synapse-analyticssplicemachine.com/­how-it-works
DeveloperApache Software FoundationDgraph Labs, Inc.MicrosoftMicrosoftSplice Machine
Initial release20182016201020162014
Current release1.1.0, April 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoMIT LicensecommercialOpen Source infoAGPL 3.0, commercial license available
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 languageJavaGo.NET and CC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
.NEThostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenonoyesyes
APIs and other access methodsJDBC
Native API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
RESTful HTTP APIADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
F#
Visual Basic
C#
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyesTransact SQLyes infoJava
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yeshorizontal partitioningSharding, horizontal partitioningShared Nothhing Auto-Sharding, Columnar 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 replicasSynchronous replication via RaftyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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 storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesno infoPlanned for future releasesyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBDgraphGraph Engine infoformer name: TrinityMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSplice Machine
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