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DBMS > InfinityDB vs. IRONdb vs. RavenDB vs. Spark SQL vs. Transbase

System Properties Comparison InfinityDB vs. IRONdb vs. RavenDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA Java embedded Key-Value Store which extends the Java Map interfaceA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value storeTime Series DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#378  Overall
#57  Key-value stores
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websiteboilerbay.comwww.circonus.com/solutions/time-series-database/ravendb.netspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-startedravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperBoiler Bay Inc.Circonus LLC.Hibernating RhinosApache Software FoundationTransaction Software GmbH
Initial release20022017201020141987
Current release4.0V0.10.20, January 20185.4, July 20223.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C#ScalaC and C++
Server operating systemsAll OS with a Java VMLinuxLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes infotext, numeric, histogramsnoyesyes
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 indexesno infomanual creation possible, using inversions based on multi-value capabilitynoyesnoyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (RQL)SQL-like DML and DDL statementsyes
APIs and other access methodsAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesJava.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoyes, in Luayesnoyes
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic, metric affinity per nodeShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneconfigurable replication factor, datacenter awareMulti-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodesDefault 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.Immediate Consistency
Foreign keys infoReferential integrityno infomanual creation possible, using inversions based on multi-value capabilitynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID, Cluster-wide transaction availablenoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnonoAuthorization levels configured per client per databasenofine grained access rights according to SQL-standard

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More resources
InfinityDBIRONdbRavenDBSpark SQLTransbase
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