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DBMS > Google Cloud Datastore vs. IRONdb vs. OrigoDB vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. IRONdb vs. OrigoDB vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonOrigoDB  Xexclude from comparisonSphinx  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 PlatformA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA fully ACID in-memory object graph databaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeTime Series DBMSDocument store
Object oriented DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/origodb.comsphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-startedorigodb.com/­docssphinxsearch.com/­docs
DeveloperGoogleCirconus LLC.Robert Friberg et alSphinx Technologies Inc.
Initial release200820172009 infounder the name LiveDB2001
Current releaseV0.10.20, January 20183.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C#C++
Server operating systemshostedLinuxLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyes infotext, numeric, histogramsUser defined using .NET types and collectionsno
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 infocan be achieved using .NET
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API.NET Client API
HTTP API
LINQ
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.NetC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App Engineyes, in Luayesno
TriggersCallbacks using the Google Apps Enginenoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodehorizontal partitioning infoclient side managed; servers are not synchronizedSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosconfigurable replication factor, datacenter awareSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes infoThe original contents of fields are not stored in the Sphinx index.
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)noRole based authorizationno

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More resources
Google Cloud DatastoreIRONdbOrigoDBSphinx
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