DBMS > Drizzle vs. Microsoft Azure SQL Data Warehouse vs. Microsoft SQL Server vs. OmniSci
System Properties Comparison Drizzle vs. Microsoft Azure SQL Data Warehouse vs. Microsoft SQL Server vs. OmniSci
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|Editorial information provided by DB-Engines|
|Name||Drizzle Xexclude from comparison||Microsoft Azure SQL Data Warehouse Xexclude from comparison||Microsoft SQL Server Xexclude from comparison||OmniSci Formerly named 'MapD', rebranded to 'OmniSci' in September 2018 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.|
|Description||MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.||Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server||Microsofts relational DBMS||A high performance, in-memory, column-oriented RDBMS, designed to run on GPUs|
|Primary database model||Relational DBMS||Relational DBMS||Relational DBMS||Relational DBMS|
|Secondary database models||Document store|
|Developer||Drizzle project, originally started by Brian Aker||Microsoft||Microsoft||MapD Technologies, Inc.|
|Current release||7.2.4, September 2012||SQL Server 2019, November 2019||V4|
|License Commercial or Open Source||Open Source GNU GPL||commercial||commercial restricted free version is available||Open Source Apache Version 2; enterprise edition available|
|Cloud-based only Only available as a cloud service||no||yes||no||no|
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|Implementation language||C++||C++||C++||C++ and CUDA|
|Server operating systems||FreeBSD|
|Typing predefined data types such as float or date||yes||yes||yes||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no||yes||no|
|SQL Support of SQL||yes with proprietary extensions||yes||yes||yes|
|APIs and other access methods||JDBC||ADO.NET|
Tabular Data Stream (TDS)
|Supported programming languages||C|
|All languages supporting JDBC/ODBC/Thrift|
|Server-side scripts Stored procedures||no||Transact SQL||Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java||no|
|Triggers||no hooks for callbacks inside the server can be used.||no||yes||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Sharding, horizontal partitioning||tables can be distributed across several files (horizontal partitioning); sharding through federation||Sharding Round robin|
|Replication methods Methods for redundantly storing data on multiple nodes||Master-master replication|
|yes||yes, but depending on the SQL-Server Edition||Master-master replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||no||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||yes||yes||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID||ACID||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes||yes|
|User concepts Access control||Pluggable authentication mechanisms e.g. LDAP, HTTP||yes||fine grained access rights according to SQL-standard||fine grained access rights according to SQL-standard|
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|Drizzle||Microsoft Azure SQL Data Warehouse||Microsoft SQL Server||OmniSci Formerly named 'MapD', rebranded to 'OmniSci' in September 2018|
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