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DBMS > Apache Druid vs. IBM Db2 Event Store vs. Microsoft Azure Table Storage vs. TDengine

System Properties Comparison Apache Druid vs. IBM Db2 Event Store vs. Microsoft Azure Table Storage vs. TDengine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed Event Store optimized for Internet of Things use casesA Wide Column Store for rapid development using massive semi-structured datasetsTime Series DBMS and big data platform
Primary database modelRelational DBMS
Time Series DBMS
Event Store
Time Series DBMS
Wide column storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Websitedruid.apache.orgwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-storedocs.tdengine.com
DeveloperApache Software Foundation and contributorsIBMMicrosoftTDEngine, previously Taos Data
Initial release2012201720122019
Current release29.0.1, April 20242.03.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree developer edition availablecommercialOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C
Server operating systemsLinux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionhostedLinux
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
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.nononono
Secondary indexesyesnonono
SQL infoSupport of SQLSQL for queryingyes infothrough the embedded Spark runtimenoStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyesnono
Triggersnononoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesActive-active shard replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesyes
More information provided by the system vendor
Apache DruidIBM Db2 Event StoreMicrosoft Azure Table StorageTDengine
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
Apache DruidIBM Db2 Event StoreMicrosoft Azure Table StorageTDengine
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