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DBMS > HugeGraph vs. IRONdb vs. Microsoft Azure Table Storage vs. Oracle Coherence vs. ReductStore

System Properties Comparison HugeGraph vs. IRONdb vs. Microsoft Azure Table Storage vs. Oracle Coherence vs. ReductStore

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOracle Coherence  Xexclude from comparisonReductStore  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA fast-speed and highly-scalable Graph DBMSA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA Wide Column Store for rapid development using massive semi-structured datasetsOracles in-memory data grid solutionDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelGraph DBMSTime Series DBMSWide column storeKey-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.97
Rank#129  Overall
#22  Key-value stores
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.circonus.com/solutions/time-series-database/azure.microsoft.com/­en-us/­services/­storage/­tableswww.oracle.com/­java/­coherencegithub.com/­reductstore
www.reduct.store
Technical documentationhugegraph.apache.org/­docsdocs.circonus.com/irondb/category/getting-starteddocs.oracle.com/­en/­middleware/­standalone/­coherencewww.reduct.store/­docs
DeveloperBaiduCirconus LLC.MicrosoftOracleReductStore LLC
Initial release20182017201220072023
Current release0.9V0.10.20, January 201814.1, August 20231.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++JavaC++, Rust
Server operating systemsLinux
macOS
Unix
LinuxhostedAll OS with a Java VMDocker
Linux
macOS
Windows
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes
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 indexesyes infoalso supports composite index and range indexnonono
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
HTTP APIRESTful HTTP APIJCache
JPA
RESTful HTTP API
HTTP API
Supported programming languagesGroovy
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyes, in Luanono
Triggersnononoyes infoLive Events
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseconfigurable replication factor, datacenter awareyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infooptionally
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlUsers, roles and permissionsnoAccess rights based on private key authentication or shared access signaturesauthentification to access the cache via certificates or http basic authentication

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More resources
HugeGraphIRONdbMicrosoft Azure Table StorageOracle CoherenceReductStore
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