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

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

Editorial information provided by DB-Engines
NameIRONdb  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonTransbase  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA 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 concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelTime Series DBMSDocument storeRelational DBMSKey-value storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.circonus.com/solutions/time-series-database/ravendb.netspark.apache.org/­sqldbmx.net/­tkrzwwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.circonus.com/irondb/category/getting-startedravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCirconus LLC.Hibernating RhinosApache Software FoundationMikio HirabayashiTransaction Software GmbH
Initial release20172010201420201987
Current releaseV0.10.20, January 20185.4, July 20223.5.0 ( 2.13), September 20230.9.3, August 2020Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0Open Source infoApache Version 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 languageC and C++C#ScalaC++C and C++
Server operating systemsLinuxLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Linux
macOS
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes infotext, numeric, histogramsnoyesnoyes
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 indexesnoyesnoyes
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (RQL)SQL-like DML and DDL statementsnoyes
APIs and other access methodsHTTP 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 languages.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++
Java
Python
Ruby
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes, in Luayesnonoyes
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareMulti-source replicationnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, 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.nonoyes infousing specific database classesno
User concepts infoAccess controlnoAuthorization levels configured per client per databasenonofine grained access rights according to SQL-standard

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More resources
IRONdbRavenDBSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTransbase
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