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DBMS > Badger vs. CouchDB vs. Microsoft Azure Synapse Analytics vs. Rockset vs. TDengine

System Properties Comparison Badger vs. CouchDB vs. Microsoft Azure Synapse Analytics vs. Rockset vs. TDengine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRockset  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA scalable, reliable search and analytics service in the cloud, built on RocksDBTime Series DBMS and big data platform
Primary database modelKey-value storeDocument storeRelational DBMSDocument storeTime Series DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionRelational DBMS
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score9.30
Rank#45  Overall
#7  Document stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgercouchdb.apache.orgazure.microsoft.com/­services/­synapse-analyticsrockset.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.couchdb.org/­en/­stabledocs.microsoft.com/­azure/­synapse-analyticsdocs.rockset.comdocs.tdengine.com
DeveloperDGraph LabsApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerMicrosoftRocksetTDEngine, previously Taos Data
Initial release20172005201620192019
Current release3.3.3, December 20233.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache version 2commercialcommercialOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoErlangC++C++C
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Android
BSD
Linux
OS X
Solaris
Windows
hostedhostedLinux
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenonoyesdynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexesnoyes infovia viewsyesall fields are automatically indexedno
SQL infoSupport of SQLnonoyesRead-only SQL queries, including JOINsStandard SQL with extensions for time-series applications
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
JDBC
ODBC
HTTP RESTJDBC
RESTful HTTP API
Supported programming languagesGoC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#
Java
PHP
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnoView functions in JavaScriptTransact SQLnono
Triggersnoyesnonoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoimproved architecture with release 2.0Sharding, horizontal partitioningAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
yesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyesyes
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.nono
User concepts infoAccess controlnoAccess rights for users can be defined per databaseyesAccess rights for users and organizations can be defined via Rockset consoleyes
More information provided by the system vendor
BadgerCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRocksetTDengine
Specific characteristicsTDengine™ 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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BadgerCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRocksetTDengine
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