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DBMS > EXASOL vs. HugeGraph vs. Ingres vs. IRONdb vs. Kinetica

System Properties Comparison EXASOL vs. HugeGraph vs. Ingres vs. IRONdb vs. Kinetica

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonHugeGraph  Xexclude from comparisonIngres  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A fast-speed and highly-scalable Graph DBMSWell established RDBMSA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSGraph DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitewww.exasol.comgithub.com/­hugegraph
hugegraph.apache.org
www.actian.com/­databases/­ingreswww.circonus.com/solutions/time-series-database/www.kinetica.com
Technical documentationwww.exasol.com/­resourceshugegraph.apache.org/­docsdocs.actian.com/­ingresdocs.circonus.com/irondb/category/getting-starteddocs.kinetica.com
DeveloperExasolBaiduActian CorporationCirconus LLC.Kinetica
Initial release200020181974 infooriginally developed at University Berkely in early 1970s20172012
Current release0.911.2, May 2022V0.10.20, January 20187.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialcommercial
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++C, C++
Server operating systemsLinux
macOS
Unix
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
LinuxLinux
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infotext, numeric, histogramsyes
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.nonono infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyes infoalso supports composite index and range indexyesnoyes
SQL infoSupport of SQLyesnoyesSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methods.Net
JDBC
ODBC
WebSocket
Java API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP APIJDBC
ODBC
RESTful HTTP API
Supported programming languagesJava
Lua
Python
R
Groovy
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsasynchronous Gremlin script jobsyesyes, in Luauser defined functions
Triggersyesnoyesnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning infoIngres Star to access multiple databases simultaneouslyAutomatic, metric affinity per nodeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseIngres Replicatorconfigurable replication factor, datacenter awareSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationvia hugegraph-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyes infoedges in graphyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
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.yesyesnonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardUsers, roles and permissionsfine grained access rights according to SQL-standardnoAccess rights for users and roles on table level

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More resources
EXASOLHugeGraphIngresIRONdbKinetica
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