DBMS > Google Cloud Datastore vs. MySQL vs. SpaceTime
System Properties Comparison Google Cloud Datastore vs. MySQL vs. SpaceTime
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|Editorial information provided by DB-Engines
|Google Cloud Datastore Xexclude from comparison
|MySQL Xexclude from comparison
|SpaceTime Xexclude from comparison
|Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
|Widely used open source RDBMS
|SpaceTime is a spatio-temporal DBMS with a focus on performance.
|Primary database model
|Relational DBMS Key/Value like access via memcached API
|Secondary database models
|Oracle since 2010, originally MySQL AB, then Sun
|8.3.0, January 2024
|License Commercial or Open Source
|Open Source GPL version 2. Commercial licenses with extended functionallity are available
|Cloud-based only Only available as a cloud service
|DBaaS offerings (sponsored links) Database as a Service
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|C and C++
|Server operating systems
|Typing predefined data types such as float or date
|yes, details here
|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.
|SQL Support of SQL
|SQL-like query language (GQL)
|yes with proprietary extensions
|A subset of ANSI SQL is implemented
|APIs and other access methods
|gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary native API
|RESTful HTTP API
|Supported programming languages
|Server-side scripts Stored procedures
|using Google App Engine
|yes proprietary syntax
|Callbacks using the Google Apps Engine
|Partitioning methods Methods for storing different data on different nodes
|horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
|Replication methods Methods for redundantly storing data on multiple nodes
|Multi-source replication using Paxos
|Real-time block device replication (DRBD)
|MapReduce Offers an API for user-defined Map/Reduce methods
|yes using Google Cloud Dataflow
|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.
|Foreign keys Referential integrity
|yes via ReferenceProperties or Ancestor paths
|yes not for MyISAM storage engine
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|ACID Serializable Isolation within Transactions, Read Committed outside of Transactions
|ACID not for MyISAM storage engine
|Concurrency Support for concurrent manipulation of data
|yes table locks or row locks depending on storage engine
|Durability Support for making data persistent
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.
|User concepts Access control
|Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
|Users with fine-grained authorization concept no user groups or roles
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