DBMS > Google Cloud Datastore vs. IBM Db2 Event Store
System Properties Comparison Google Cloud Datastore vs. IBM Db2 Event Store
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|Editorial information provided by DB-Engines|
|Name||Google Cloud Datastore Xexclude from comparison||IBM Db2 Event Store Xexclude from comparison|
|Description||Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform||Distributed Event Store optimized for Internet of Things use cases|
|Primary database model||Document store||Event Store|
Time Series DBMS
|License Commercial or Open Source||commercial||commercial free developer edition available|
|Cloud-based only Only available as a cloud service||yes||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Implementation language||C and C++|
|Server operating systems||hosted||Linux Linux, macOS, Windows for the developer addition|
|Typing predefined data types such as float or date||yes, details here||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||no|
|SQL Support of SQL||SQL-like query language (GQL)||yes through the embedded Spark runtime|
|APIs and other access methods||gRPC (using protocol buffers) API|
RESTful HTTP/JSON API
RESTful HTTP API
|Supported programming languages||.Net|
|Server-side scripts Stored procedures||using Google App Engine||yes|
|Triggers||Callbacks using the Google Apps Engine||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||Multi-source replication using Paxos||Active-active shard replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes using Google Cloud Dataflow||no|
|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.||Eventual Consistency|
|Foreign keys Referential integrity||yes via ReferenceProperties or Ancestor paths||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID Serializable Isolation within Transactions, Read Committed outside of Transactions||no|
|Concurrency Support for concurrent manipulation of data||yes||No - written data is immutable|
|Durability Support for making data persistent||yes||Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage|
|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|
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|Google Cloud Datastore||IBM Db2 Event Store|
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