DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. OpenQM
System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. OpenQM
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|Editorial information provided by DB-Engines|
|Name||Google Cloud Datastore Xexclude from comparison||Hawkular Metrics Xexclude from comparison||OpenQM also called QM Xexclude from comparison|
|Description||Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform||Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.||QpenQM is a high-performance, self-tuning, multi-value DBMS|
|Primary database model||Document store||Time Series DBMS||Multivalue DBMS|
|Developer||Community supported by Red Hat||Rocket Software, originally Martin Phillips|
|License Commercial or Open Source||commercial||Open Source Apache 2.0||Open Source GPLv2, extended commercial license available|
|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|
|Data scheme||schema-free||schema-free||yes with some exceptions|
|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||yes|
|SQL Support of SQL||SQL-like query language (GQL)||no||no|
|APIs and other access methods||gRPC (using protocol buffers) API|
RESTful HTTP/JSON API
|Supported programming languages||.Net|
|Server-side scripts Stored procedures||using Google App Engine||no||yes|
|Triggers||Callbacks using the Google Apps Engine||yes via Hawkular Alerting||yes|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Sharding based on Cassandra||yes|
|Replication methods Methods for redundantly storing data on multiple nodes||Multi-source replication using Paxos||selectable replication factor based on Cassandra||yes|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes using Google Cloud Dataflow||no||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 based on Cassandra|
Immediate Consistency based on Cassandra
|Foreign keys Referential integrity||yes via ReferenceProperties or Ancestor paths||no||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||ACID|
|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||no|
|User concepts Access control||Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)||no||Access rights can be defined down to the item level|
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|Google Cloud Datastore||Hawkular Metrics||OpenQM also called QM|
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