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DBMS > Graph Engine vs. IRONdb vs. NSDb vs. RavenDB

System Properties Comparison Graph Engine vs. IRONdb vs. NSDb vs. RavenDB

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonIRONdb  Xexclude from comparisonNSDb  Xexclude from comparisonRavenDB  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelGraph DBMS
Key-value store
Time Series DBMSTime Series DBMSDocument store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitewww.graphengine.iowww.circonus.com/solutions/time-series-database/nsdb.ioravendb.net
Technical documentationwww.graphengine.io/­docs/­manualdocs.circonus.com/irondb/category/getting-startednsdb.io/­Architectureravendb.net/­docs
DeveloperMicrosoftCirconus LLC.Hibernating Rhinos
Initial release2010201720172010
Current releaseV0.10.20, January 20185.4, July 2022
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2.0Open Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CC and C++Java, ScalaC#
Server operating systems.NETLinuxLinux
macOS
Linux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes: int, bigint, decimal, stringno
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 indexesnoall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query languageSQL-like query language (RQL)
APIs and other access methodsRESTful HTTP APIHTTP APIgRPC
HTTP REST
WebSocket
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC#
C++
F#
Visual Basic
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyes, in Luanoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningAutomatic, metric affinity per nodeShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesEventual ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnoAuthorization levels configured per client per database

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More resources
Graph Engine infoformer name: TrinityIRONdbNSDbRavenDB
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Trinity
30 October 2010, Microsoft

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