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DBMS > DataFS vs. Google Cloud Datastore vs. Ignite vs. IRONdb

System Properties Comparison DataFS vs. Google Cloud Datastore vs. Ignite vs. IRONdb

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIgnite  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelObject oriented DBMSDocument storeKey-value store
Relational DBMS
Time Series DBMS
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitenewdatabase.comcloud.google.com/­datastoreignite.apache.orgwww.circonus.com/solutions/time-series-database/
Technical documentationdev.mobiland.com/­Overview.xspcloud.google.com/­datastore/­docsapacheignite.readme.io/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperMobiland AGGoogleApache Software FoundationCirconus LLC.
Initial release2018200820152017
Current release1.1.263, October 2022Apache Ignite 2.6V0.10.20, January 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetC and C++
Server operating systemsWindowshostedLinux
OS X
Solaris
Windows
Linux
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infotext, numeric, histograms
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 indexesnoyesyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)yes, in Lua
Triggersno, except callback-events from server when changes happenedCallbacks using the Google Apps Engineyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)configurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
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 controlWindows-ProfileAccess 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
DataFSGoogle Cloud DatastoreIgniteIRONdb
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