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DBMS > Google Cloud Datastore vs. Google Cloud Spanner vs. GridGain vs. Hawkular Metrics

System Properties Comparison Google Cloud Datastore vs. Google Cloud Spanner vs. GridGain vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonGridGain  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.GridGain is an in-memory computing platform, built on Apache IgniteHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelDocument storeRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Websitecloud.google.com/­datastorecloud.google.com/­spannerwww.gridgain.comwww.hawkular.org
Technical documentationcloud.google.com/­datastore/­docscloud.google.com/­spanner/­docswww.gridgain.com/­docs/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperGoogleGoogleGridGain Systems, Inc.Community supported by Red Hat
Initial release2008201720072014
Current releaseGridGain 8.5.1
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJava
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)yes infoQuery statements complying to ANSI 2011ANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP REST
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Enginenoyes (compute grid and cache interceptors can be used instead)no
TriggersCallbacks using the Google Apps Enginenoyes (cache interceptors and events)yes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication with 3 replicas for regional instances.yes (replicated cache)selectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong 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 ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoStrict serializable isolationACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsno

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More resources
Google Cloud DatastoreGoogle Cloud SpannerGridGainHawkular Metrics
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