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DBMS > Amazon DocumentDB vs. Faircom DB vs. Solr vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Faircom DB vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeKey-value store
Relational DBMS
Search engineSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.faircom.com/­products/­faircom-dbsolr.apache.orgsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperFairCom CorporationApache Software FoundationSphinx Technologies Inc.
Initial release2019197920062001
Current releaseV12, November 20209.6.0, April 20243.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaC++
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes infosupports customizable data types and automatic typingno
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.nonoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++Java pluginsno
Triggersnoyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingSharding 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, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationstunable from ACID to Eventually Consistentoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes 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.yesyes
User concepts infoAccess controlAccess rights for users and rolesFine grained access rights according to SQL-standard with additional protections for filesyesno

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More resources
Amazon DocumentDBFaircom DB infoformerly c-treeACESolrSphinx
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