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DBMS > HugeGraph vs. Ingres vs. IRONdb vs. Spark SQL vs. Trafodion

System Properties Comparison HugeGraph vs. Ingres vs. IRONdb vs. Spark SQL vs. Trafodion

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonIngres  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA fast-speed and highly-scalable Graph DBMSWell established RDBMSA 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 processingTransactional SQL-on-Hadoop DBMS
Primary database modelGraph DBMSRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.actian.com/­databases/­ingreswww.circonus.com/solutions/time-series-database/spark.apache.org/­sqltrafodion.apache.org
Technical documentationhugegraph.apache.org/­docsdocs.actian.com/­ingresdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperBaiduActian CorporationCirconus LLC.Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release20181974 infooriginally developed at University Berkely in early 1970s201720142014
Current release0.911.2, May 2022V0.10.20, January 20183.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
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 languageJavaCC and C++ScalaC++, Java
Server operating systemsLinux
macOS
Unix
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
LinuxLinux
OS X
Windows
Linux
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes 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.nono infobut tools for importing/exporting data from/to XML-files availablenonono
Secondary indexesyes infoalso supports composite index and range indexyesnonoyes
SQL infoSupport of SQLnoyesSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
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
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyesyes, in LuanoJava Stored Procedures
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning infoIngres Star to access multiple databases simultaneouslyAutomatic, metric affinity per nodeyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseIngres Replicatorconfigurable replication factor, datacenter awarenoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
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.yesnononono
User concepts infoAccess controlUsers, roles and permissionsfine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard

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More resources
HugeGraphIngresIRONdbSpark SQLTrafodion
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