DBMS > Amazon Neptune vs. Google Cloud Datastore
System Properties Comparison Amazon Neptune vs. Google Cloud Datastore
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|Editorial information provided by DB-Engines|
|Name||Amazon Neptune Xexclude from comparison||Google Cloud Datastore Xexclude from comparison|
|Description||Fast, reliable graph database built for the cloud||Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform|
|Primary database model||Graph DBMS|
|License Commercial or Open Source||commercial||commercial|
|Cloud-based only Only available as a cloud service||yes||yes|
|DBaaS offerings (sponsored links) Database as a Service|
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|Server operating systems||hosted||hosted|
|Typing predefined data types such as float or date||yes||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.||no||no|
|SQL Support of SQL||no||SQL-like query language (GQL)|
|APIs and other access methods||OpenCypher|
RDF 1.1 / SPARQL 1.1
|gRPC (using protocol buffers) API|
RESTful HTTP/JSON API
|Supported programming languages||C#|
|Server-side scripts Stored procedures||no||using Google App Engine|
|Triggers||no||Callbacks using the Google Apps Engine|
|Partitioning methods Methods for storing different data on different nodes||none||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.||Multi-source replication using Paxos|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||yes using Google Cloud Dataflow|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||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 Relationships in graphs||yes via ReferenceProperties or Ancestor paths|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID Serializable Isolation within Transactions, Read Committed outside of Transactions|
|Concurrency Support for concurrent manipulation of data||yes||yes|
|Durability Support for making data persistent||yes with encyption-at-rest||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no|
|User concepts Access control||Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)||Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)|
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|Amazon Neptune||Google Cloud Datastore|
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