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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. PouchDB vs. STSdb vs. Teradata Aster

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. PouchDB vs. STSdb vs. Teradata Aster

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPouchDB  Xexclude from comparisonSTSdb  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.JavaScript DBMS with an API inspired by CouchDBKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeTime Series DBMSDocument storeKey-value storeRelational DBMS
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
Score2.28
Rank#115  Overall
#21  Document stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitecloud.google.com/­datastorewww.hawkular.orgpouchdb.comgithub.com/­STSSoft/­STSdb4
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidepouchdb.com/­guides
DeveloperGoogleCommunity supported by Red HatApache Software FoundationSTS Soft SCTeradata
Initial release20082014201220112005
Current release7.1.1, June 20194.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoGPLv2, commercial license availablecommercial
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 languageJavaJavaScriptC#
Server operating systemshostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)WindowsLinux
Data schemeschema-freeschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes, details hereyesnoyes infoprimitive types and user defined types (classes)yes
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.nononoyes infoin Aster File Store
Secondary indexesyesnoyes infovia viewsnoyes
SQL infoSupport of SQLSQL-like query language (GQL)nononoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTHTTP REST infoonly for PouchDB Server
JavaScript API
.NET Client APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
JavaScriptC#
Java
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresusing Google App EnginenoView functions in JavaScriptnoR packages
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infowith a proxy-based framework, named couchdb-loungenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandraMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesnoyes infoSQL Map-Reduce Framework
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
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)nononofine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreHawkular MetricsPouchDBSTSdbTeradata Aster
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