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DBMS > Apache Impala vs. Apache IoTDB vs. Drizzle vs. Microsoft SQL Server vs. SQL.JS

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Drizzle vs. Microsoft SQL Server vs. SQL.JS

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSQL.JS  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Microsofts flagship relational DBMSPort of SQLite to JavaScript
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score829.80
Rank#3  Overall
#3  Relational DBMS
Score0.57
Rank#248  Overall
#114  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgwww.microsoft.com/­en-us/­sql-serversql.js.org
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmllearn.microsoft.com/­en-US/­sql/­sql-serversql.js.org/­documentation/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationDrizzle project, originally started by Brian AkerMicrosoftAlon Zakai infoenhancements implemented by others
Initial release20132018200819892012
Current release4.1.0, June 20221.1.0, April 20237.2.4, September 2012SQL Server 2022, November 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoGNU GPLcommercial inforestricted free version is availableOpen Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++C++JavaScript
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Linux
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyes infowith proprietary extensionsyesyes infoSQL-92 is not fully supported
APIs and other access methodsJDBC
ODBC
JDBC
Native API
JDBCADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JavaScript API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersnoyesno infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingtables can be distributed across several files (horizontal partitioning); sharding through federationnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
yes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistencynone
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesno infoexcept by serializing a db to a file
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardno

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More resources
Apache ImpalaApache IoTDBDrizzleMicrosoft SQL ServerSQL.JS
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