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DBMS > Amazon DocumentDB vs. Atos Standard Common Repository vs. BigchainDB vs. Sphinx vs. Sqrrl

System Properties Comparison Amazon DocumentDB vs. Atos Standard Common Repository vs. BigchainDB vs. Sphinx vs. Sqrrl

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonBigchainDB  Xexclude from comparisonSphinx  Xexclude from comparisonSqrrl  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsOpen source search engine for searching in data from different sources, e.g. relational databasesAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument storeDocument store
Key-value store
Document storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.79
Rank#212  Overall
#36  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.bigchaindb.comsphinxsearch.comsqrrl.com
Technical documentationaws.amazon.com/­documentdb/­resourcesbigchaindb.readthedocs.io/­en/­latestsphinxsearch.com/­docs
DeveloperAtos Convergence CreatorsSphinx Technologies Inc.Amazon infooriginally Sqrrl Data, Inc.
Initial release20192016201620012012
Current release17033.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL v3Open Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaPythonC++Java
Server operating systemshostedLinuxLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeSchema and schema-less with LDAP viewsschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesoptionalnonoyes
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.noyesno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)no
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)LDAPCLI Client
RESTful HTTP API
Proprietary protocolAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages with LDAP bindingsGo
Haskell
Java
JavaScript
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnononono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesselectable replication factornoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic execution of specific operationsnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes,with MongoDB ord RethinkDByes 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.yes
User concepts infoAccess controlAccess rights for users and rolesLDAP bind authenticationyesnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon DocumentDBAtos Standard Common RepositoryBigchainDBSphinxSqrrl
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