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

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

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonInfinityDB  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 DBMSA Java embedded Key-Value Store which extends the Java Map interfaceA 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 DBMSKey-value storeTime 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
Score0.00
Rank#378  Overall
#57  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
boilerbay.comwww.circonus.com/solutions/time-series-database/spark.apache.org/­sqltrafodion.apache.org
Technical documentationhugegraph.apache.org/­docsboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperBaiduBoiler Bay Inc.Circonus LLC.Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release20182002201720142014
Current release0.94.0V0.10.20, 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

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Implementation languageJavaJavaC and C++ScalaC++, Java
Server operating systemsLinux
macOS
Unix
All OS with a Java VMLinuxLinux
OS X
Windows
Linux
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes 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.nonononono
Secondary indexesyes infoalso supports composite index and range indexno infomanual creation possible, using inversions based on multi-value capabilitynonoyes
SQL infoSupport of SQLnonoSQL-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
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesGroovy
Java
Python
Java.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 jobsnoyes, in LuanoJava Stored Procedures
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBasenoneAutomatic, 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 HBasenoneconfigurable 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 Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphno infomanual creation possible, using inversions based on multi-value capabilitynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnonoACID
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.yesnononono
User concepts infoAccess controlUsers, roles and permissionsnononofine grained access rights according to SQL-standard

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More resources
HugeGraphInfinityDBIRONdbSpark SQLTrafodion
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