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DBMS > FeatureBase vs. Graph Engine vs. InfinityDB vs. IRONdb

System Properties Comparison FeatureBase vs. Graph Engine vs. InfinityDB vs. IRONdb

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA Java embedded Key-Value Store which extends the Java Map interfaceA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelRelational DBMSGraph DBMS
Key-value store
Key-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score0.08
Rank#365  Overall
#55  Key-value stores
Websitewww.featurebase.comwww.graphengine.ioboilerbay.comwww.circonus.com/solutions/time-series-database/
Technical documentationdocs.featurebase.comwww.graphengine.io/­docs/­manualboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-started
DeveloperMolecula and Pilosa Open Source ContributorsMicrosoftBoiler Bay Inc.Circonus LLC.
Initial release2017201020022017
Current release2022, May 20224.0V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoMIT Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGo.NET and CJavaC and C++
Server operating systemsLinux
macOS
.NETAll OS with a Java VMLinux
Data schemeyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes 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.nononono
Secondary indexesnono infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLSQL queriesnonoSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
RESTful HTTP APIAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP API
Supported programming languagesJava
Python
C#
C++
F#
Visual Basic
Java.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 proceduresyesnoyes, in Lua
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningnoneAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesnono infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlnono

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More resources
FeatureBaseGraph Engine infoformer name: TrinityInfinityDBIRONdb
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