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DBMS > Hypertable vs. Ignite vs. IRONdb vs. Spark SQL vs. Transbase

System Properties Comparison Hypertable vs. Ignite vs. IRONdb vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonIgnite  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelWide column storeKey-value store
Relational DBMS
Time Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websiteignite.apache.orgwww.circonus.com/solutions/time-series-database/spark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationapacheignite.readme.io/­docsdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperHypertable Inc.Apache Software FoundationCirconus LLC.Apache Software FoundationTransaction Software GmbH
Initial release20092015201720141987
Current release0.9.8.11, March 2016Apache Ignite 2.6V0.10.20, January 20183.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0commercialOpen 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 languageC++C++, Java, .NetC and C++ScalaC and C++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes 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.yesnonono
Secondary indexesrestricted infoonly exact value or prefix value scansyesnonoyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methodsC++ API
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yes, in Luanoyes
Triggersnoyes (cache interceptors and events)nonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelyes (replicated cache)configurable replication factor, datacenter awarenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoyes
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.yesnonono
User concepts infoAccess controlnoSecurity Hooks for custom implementationsnonofine grained access rights according to SQL-standard

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More resources
HypertableIgniteIRONdbSpark SQLTransbase
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