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DBMS > HugeGraph vs. Ignite vs. Riak KV vs. Spark SQL

System Properties Comparison HugeGraph vs. Ignite vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonIgnite  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Distributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMSKey-value store
Relational DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.orgspark.apache.org/­sql
Technical documentationhugegraph.apache.org/­docsapacheignite.readme.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBaiduApache Software FoundationOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2018201520092014
Current release0.9Apache Ignite 2.63.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .NetErlangScala
Server operating systemsLinux
macOS
Unix
Linux
OS X
Solaris
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyesnono
Secondary indexesyes infoalso supports composite index and range indexyesrestrictedno
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesGroovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)Erlangno
Triggersnoyes (cache interceptors and events)yes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes (replicated cache)selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparkyes (compute grid and hadoop accelerator)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoedges in graphnono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlUsers, roles and permissionsSecurity Hooks for custom implementationsyes, using Riak Securityno

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HugeGraphIgniteRiak KVSpark SQL
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