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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBangdb  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonWarp 10  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 FlinkConverged and high performance database for device data, events, time series, document and graphGridGain 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 modelTime Series DBMSDocument store
Graph DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  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
Websiteiotdb.apache.orgbangdb.comwww.gridgain.comazure.microsoft.com/­services/­synapse-analyticswww.warp10.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bangdb.comwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­azure/­synapse-analyticswww.warp10.io/­content/­02_Getting_started
DeveloperApache Software FoundationSachin Sinha, BangDBGridGain Systems, Inc.MicrosoftSenX
Initial release20182012200720162015
Current release1.1.0, April 2023BangDB 2.0, October 2021GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3commercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++Java, C++, .NetC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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 indexesyesyes infosecondary, composite, nested, reverse, geospatialyesyesno
SQL infoSupport of SQLSQL-like query languageSQL like support with command line toolANSI-99 for query and DML statements, subset of DDLyesno
APIs and other access methodsJDBC
Native API
Proprietary protocol
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
PHP
Server-side scripts infoStored proceduresyesnoyes (compute grid and cache interceptors can be used instead)Transact SQLyes infoWarpScript
Triggersyesyes, Notifications (with Streaming only)yes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding, 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 replicasselectable replication factor, Knob for CAP (enterprise version only)yes (replicated cache)yesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Tunable consistency, set CAP knob accordinglyImmediate 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 datanoACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modeyesyes
User concepts infoAccess controlyesyes (enterprise version only)Security Hooks for custom implementationsyesMandatory use of cryptographic tokens, containing fine-grained authorizations

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