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DBMS > Apache IoTDB vs. Badger vs. KeyDB vs. Microsoft Azure Synapse Analytics vs. UniData,UniVerse

System Properties Comparison Apache IoTDB vs. Badger vs. KeyDB vs. Microsoft Azure Synapse Analytics vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBadger  Xexclude from comparisonKeyDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonUniData,UniVerse  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 FlinkAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelTime Series DBMSKey-value storeKey-value storeRelational DBMSMultivalue DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websiteiotdb.apache.orggithub.com/­dgraph-io/­badgergithub.com/­Snapchat/­KeyDB
keydb.dev
azure.microsoft.com/­services/­synapse-analyticswww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.keydb.devdocs.microsoft.com/­azure/­synapse-analyticsdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperApache Software FoundationDGraph LabsEQ Alpha Technology Ltd.MicrosoftRocket Software
Initial release20182017201920161985
Current release1.1.0, April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoBSD-3commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++C++C
Server operating systemsAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Solaris
Windows
LinuxhostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnopartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyesoptional
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 indexesyesnoyes infoby using the Redis Search moduleyesyes
SQL infoSupport of SQLSQL-like query languagenonoyesyes
APIs and other access methodsJDBC
Native API
Proprietary protocol infoRESP - REdis Serialization ProtocoADO.NET
JDBC
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
GoC
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C#
Java
PHP
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyesnoLuaTransact SQLyes
Triggersyesnononoyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneMulti-source replication
Source-replica replication
yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
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 datanonoOptimistic locking, atomic execution of commands blocks and scriptsACIDACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesnosimple password-based access control and ACLyesAccess rights according to SQL-standard and operating system based

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More resources
Apache IoTDBBadgerKeyDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseUniData,UniVerse
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