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DBMS > Amazon DocumentDB vs. Apache Druid vs. HugeGraph vs. mSQL vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Apache Druid vs. HugeGraph vs. mSQL vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Druid  Xexclude from comparisonHugeGraph  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA fast-speed and highly-scalable Graph DBMSmSQL (Mini SQL) is a simple and lightweight RDBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMS
Time Series DBMS
Graph DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbdruid.apache.orggithub.com/­hugegraph
hugegraph.apache.org
hughestech.com.au/­products/­msqlsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdruid.apache.org/­docs/­latest/­designhugegraph.apache.org/­docssphinxsearch.com/­docs
DeveloperApache Software Foundation and contributorsBaiduHughes TechnologiesSphinx Technologies Inc.
Initial release20192012201819942001
Current release29.0.1, April 20240.94.4, October 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache Version 2.0commercial infofree licenses can be providedOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCC++
Server operating systemshostedLinux
OS X
Unix
Linux
macOS
Unix
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono
Secondary indexesyesyesyes infoalso supports composite index and range indexyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL for queryingnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
Groovy
Java
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoasynchronous Gremlin script jobsnono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedyes infodepending on used storage backend, e.g. Cassandra and HBasenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes, via HDFS, S3 or other storage enginesyes infodepending on used storage backend, e.g. Cassandra and HBasenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)novia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistencynone
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users and rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemUsers, roles and permissionsnono

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More resources
Amazon DocumentDBApache DruidHugeGraphmSQL infoMini SQLSphinx
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