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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. IRONdb vs. SQL.JS vs. STSdb

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. IRONdb vs. SQL.JS vs. STSdb

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonIRONdb  Xexclude from comparisonSQL.JS  Xexclude from comparisonSTSdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded 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.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityPort of SQLite to JavaScriptKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument storeTime Series DBMSTime Series DBMSRelational DBMSKey-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
Score0.53
Rank#252  Overall
#116  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitecloud.google.com/­datastorewww.hawkular.orgwww.circonus.com/solutions/time-series-database/sql.js.orggithub.com/­STSSoft/­STSdb4
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.circonus.com/irondb/category/getting-startedsql.js.org/­documentation/­index.html
DeveloperGoogleCommunity supported by Red HatCirconus LLC.Alon Zakai infoenhancements implemented by othersSTS Soft SC
Initial release20082014201720122011
Current releaseV0.10.20, January 20184.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen SourceOpen 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 languageJavaC and C++JavaScriptC#
Server operating systemshostedLinux
OS X
Windows
Linuxserver-less, requires a JavaScript environment (browser, Node.js)Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyes infotext, numeric, histogramsyesyes 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.nononono
Secondary indexesyesnonono
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query language (Circonus Analytics Query Language: CAQL)yes infoSQL-92 is not fully supportedno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTHTTP APIJavaScript API.NET Client API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
JavaScriptC#
Java
Server-side scripts infoStored proceduresusing Google App Enginenoyes, in Luanono
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraAutomatic, metric affinity per nodenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandraconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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
Immediate consistency per node, eventual consistency across nodesnone
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesno infoexcept by serializing a db to a fileyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nononono

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More resources
Google Cloud DatastoreHawkular MetricsIRONdbSQL.JSSTSdb
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