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DBMS > Apache IoTDB vs. Bangdb vs. InfinityDB vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Bangdb vs. InfinityDB vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBangdb  Xexclude from comparisonInfinityDB  Xexclude from comparisonTimescaleDB  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 graphA Java embedded Key-Value Store which extends the Java Map interfaceA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSDocument store
Graph DBMS
Time Series DBMS
Key-value storeTime Series DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteiotdb.apache.orgbangdb.comboilerbay.comwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bangdb.comboilerbay.com/­infinitydb/­manualdocs.timescale.com
DeveloperApache Software FoundationSachin Sinha, BangDBBoiler Bay Inc.Timescale
Initial release2018201220022017
Current release1.1.0, April 2023BangDB 2.0, October 20214.02.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAll OS with a Java VMLinux
OS X
Windows
Data schemeyesschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialno infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLSQL-like query languageSQL like support with command line toolnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
Proprietary protocol
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Python
Java.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes, Notifications (with Streaming only)noyes
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 algorithmnoneyes, across time and space (hash partitioning) attributes
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)noneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Tunable consistency, set CAP knob accordinglyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
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 modenono
User concepts infoAccess controlyesyes (enterprise version only)nofine grained access rights according to SQL-standard

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More resources
Apache IoTDBBangdbInfinityDBTimescaleDB
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