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DBMS > Apache Impala vs. Drizzle vs. Microsoft Azure SQL Database vs. TimescaleDB

System Properties Comparison Apache Impala vs. Drizzle vs. Microsoft Azure SQL Database vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTimescaleDB  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 HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Database as a Service offering with high compatibility to Microsoft SQL ServerA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteimpala.apache.orgazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­azure-sqldocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerMicrosoftTimescale
Initial release2013200820102017
Current release4.1.0, June 20227.2.4, September 2012V122.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++C
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
JDBCADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoTransact SQLuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnono infohooks for callbacks inside the server can be used.yesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
yes, with always 3 replicas availableSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache ImpalaDrizzleMicrosoft Azure SQL Database infoformerly SQL AzureTimescaleDB
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