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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. HugeGraph vs. Memcached vs. STSdb

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. HugeGraph vs. Memcached vs. STSdb

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHugeGraph  Xexclude from comparisonMemcached  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A fast-speed and highly-scalable Graph DBMSIn-memory key-value store, originally intended for cachingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument storeTime Series DBMSGraph DBMSKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score19.42
Rank#32  Overall
#4  Key-value stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitecloud.google.com/­datastorewww.hawkular.orggithub.com/­hugegraph
hugegraph.apache.org
www.memcached.orggithub.com/­STSSoft/­STSdb4
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidehugegraph.apache.org/­docsgithub.com/­memcached/­memcached/­wiki
DeveloperGoogleCommunity supported by Red HatBaiduDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalSTS Soft SC
Initial release20082014201820032011
Current release0.91.6.27, May 20244.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoBSD licenseOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaCC#
Server operating systemshostedLinux
OS X
Windows
Linux
macOS
Unix
FreeBSD
Linux
OS X
Unix
Windows
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyesnoyes infoprimitive types and user defined types (classes)
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.nonono
Secondary indexesyesnoyes infoalso supports composite index and range indexnono
SQL infoSupport of SQLSQL-like query language (GQL)nononono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJava API
RESTful HTTP API
TinkerPop Gremlin
Proprietary protocol.NET Client API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
Groovy
Java
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
Java
Server-side scripts infoStored proceduresusing Google App Enginenoasynchronous Gremlin script jobsnono
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrayes infodepending on used storage backend, e.g. Cassandra and HBasenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes infodepending on used storage backend, e.g. Cassandra and HBasenone infoRepcached, a Memcached patch, provides this functionallitynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownovia hugegraph-sparknono
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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUsers, roles and permissionsyes infousing SASL (Simple Authentication and Security Layer) protocolno

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More resources
Google Cloud DatastoreHawkular MetricsHugeGraphMemcachedSTSdb
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