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DBMS > etcd vs. Microsoft Azure Table Storage vs. OpenEdge vs. Splice Machine vs. TDengine

System Properties Comparison etcd vs. Microsoft Azure Table Storage vs. OpenEdge vs. Splice Machine vs. TDengine

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparisonSplice Machine  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionA distributed reliable key-value storeA Wide Column Store for rapid development using massive semi-structured datasetsApplication development environment with integrated database management systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTime Series DBMS and big data platform
Primary database modelKey-value storeWide column storeRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgesplicemachine.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
documentation.progress.com/­output/­ua/­OpenEdge_latestsplicemachine.com/­how-it-worksdocs.tdengine.com
DeveloperMicrosoftProgress Software CorporationSplice MachineTDEngine, previously Taos Data
Initial release2012198420142019
Current release3.4, August 2019OpenEdge 12.2, March 20203.1, March 20213.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.nonoyesno
Secondary indexesnonoyesyesno
SQL infoSupport of SQLnonoyes infoclose to SQL 92yesStandard SQL with extensions for time-series applications
APIs and other access methodsgRPC
JSON over HTTP
RESTful HTTP APIJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
JDBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language)C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoyesyes infoJavano
Triggersyes, watching key changesnoyesyesyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4Shared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesUsers and groupsAccess rights for users, groups and roles according to SQL-standardyes
More information provided by the system vendor
etcdMicrosoft Azure Table StorageOpenEdgeSplice MachineTDengine
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
etcdMicrosoft Azure Table StorageOpenEdgeSplice MachineTDengine
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