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DBMS > HugeGraph vs. Ignite vs. KeyDB vs. Sphinx vs. Tkrzw

System Properties Comparison HugeGraph vs. Ignite vs. KeyDB vs. Sphinx vs. Tkrzw

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonIgnite  Xexclude from comparisonKeyDB  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsOpen source search engine for searching in data from different sources, e.g. relational databasesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelGraph DBMSKey-value store
Relational DBMS
Key-value storeSearch engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
sphinxsearch.comdbmx.net/­tkrzw
Technical documentationhugegraph.apache.org/­docsapacheignite.readme.io/­docsdocs.keydb.devsphinxsearch.com/­docs
DeveloperBaiduApache Software FoundationEQ Alpha Technology Ltd.Sphinx Technologies Inc.Mikio Hirabayashi
Initial release20182015201920012020
Current release0.9Apache Ignite 2.63.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoBSD-3Open Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .NetC++C++C++
Server operating systemsLinux
macOS
Unix
Linux
OS X
Solaris
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesnono
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 indexyesyes infoby using the Redis Search moduleyes infofull-text index on all search fields
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (SphinxQL)no
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol infoRESP - REdis Serialization ProtocoProprietary protocol
Supported programming languagesGroovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)Luanono
Triggersnoyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes (replicated cache)Multi-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparkyes (compute grid and hadoop accelerator)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDOptimistic locking, atomic execution of commands blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infousing specific database classes
User concepts infoAccess controlUsers, roles and permissionsSecurity Hooks for custom implementationssimple password-based access control and ACLnono

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More resources
HugeGraphIgniteKeyDBSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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