DBMS > Drizzle vs. Google Cloud Spanner vs. Microsoft SQL Server vs. WakandaDB
System Properties Comparison Drizzle vs. Google Cloud Spanner vs. Microsoft SQL Server vs. WakandaDB
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|Editorial information provided by DB-Engines|
|Name||Drizzle Xexclude from comparison||Google Cloud Spanner Xexclude from comparison||Microsoft SQL Server Xexclude from comparison||WakandaDB 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.|
|Primary database model||Relational DBMS||Relational DBMS||Relational DBMS||Object oriented DBMS|
|Secondary database models||Document store|
|Developer||Drizzle project, originally started by Brian Aker||Microsoft||Wakanda SAS|
|Current release||7.2.4, September 2012||SQL Server 2019, November 2019||2.7.0 (April 29, 2019), 2019|
|License Commercial or Open Source||Open Source GNU GPL||commercial||commercial restricted free version is available||Open Source AGPLv3, extended commercial license available|
|Cloud-based only Only available as a cloud service||no||yes||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|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 Query statements complying to ANSI 2011||yes||no|
|APIs and other access methods||JDBC||gRPC (using protocol buffers) API|
JDBC At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Tabular Data Stream (TDS)
|RESTful HTTP API|
|Supported programming languages||C|
|Server-side scripts Stored procedures||no||no||Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java||yes|
|Triggers||no hooks for callbacks inside the server can be used.||no||yes||yes|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Sharding||tables can be distributed across several files (horizontal partitioning); sharding through federation||none|
|Replication methods Methods for redundantly storing data on multiple nodes||Multi-source replication|
|Multi-source replication with 3 replicas for regional instances.||yes, but depending on the SQL-Server Edition||none|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||yes using Google Cloud Dataflow||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||yes||yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity||yes|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID Strict serializable isolation||ACID||ACID|
|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.||no||yes||no|
|User concepts Access control||Pluggable authentication mechanisms e.g. LDAP, HTTP||Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)||fine grained access rights according to SQL-standard||yes|
More information provided by the system vendor
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|Related products and services|
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|Drizzle||Google Cloud Spanner||Microsoft SQL Server||WakandaDB|
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