DBMS > Google Cloud Datastore vs. Microsoft SQL Server vs. Sqrrl
System Properties Comparison Google Cloud Datastore vs. Microsoft SQL Server vs. Sqrrl
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|Editorial information provided by DB-Engines|
|Name||Google Cloud Datastore Xexclude from comparison||Microsoft SQL Server Xexclude from comparison||Sqrrl Xexclude from comparison|
|Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.|
|Description||Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform||Microsofts flagship relational DBMS||Adaptable, secure NoSQL built on Apache Accumulo|
|Primary database model||Document store||Relational DBMS||Document store|
Wide column store
|Secondary database models||Document store|
|Developer||Microsoft||Amazon originally Sqrrl Data, Inc.|
|Current release||SQL Server 2019, November 2019|
|License Commercial or Open Source||commercial||commercial restricted free version is available||commercial|
|Cloud-based only Only available as a cloud service||yes||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Server operating systems||hosted||Linux|
|Typing predefined data types such as float or date||yes, details here||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|
|SQL Support of SQL||SQL-like query language (GQL)||yes||no|
|APIs and other access methods||gRPC (using protocol buffers) API|
RESTful HTTP/JSON API
Tabular Data Stream (TDS)
RESTful HTTP API
|Supported programming languages||.Net|
C using GLib
|Server-side scripts Stored procedures||using Google App Engine||Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java||no|
|Triggers||Callbacks using the Google Apps Engine||yes||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||tables can be distributed across several files (horizontal partitioning); sharding through federation||Sharding making use of Hadoop|
|Replication methods Methods for redundantly storing data on multiple nodes||Multi-source replication using Paxos||yes, but depending on the SQL-Server Edition||selectable replication factor making use of Hadoop|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes using Google Cloud Dataflow||no||yes|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency or Eventual Consistency depending on type of query and configuration Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.||Immediate Consistency||Immediate Consistency Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.|
|Foreign keys Referential integrity||yes via ReferenceProperties or Ancestor paths||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID Serializable Isolation within Transactions, Read Committed outside of Transactions||ACID||Atomic updates per row, document, or graph entity|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no||yes|
|User concepts Access control||Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)||fine grained access rights according to SQL-standard||Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)|
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|Google Cloud Datastore||Microsoft SQL Server||Sqrrl|
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