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DBMS > Amazon DocumentDB vs. Datomic vs. Qdrant vs. Sadas Engine vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Datomic vs. Qdrant vs. Sadas Engine vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatomic  Xexclude from comparisonQdrant  Xexclude from comparisonSadas Engine  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA high-performance vector database with neural network or semantic-based matchingSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSVector DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.datomic.comgithub.com/­qdrant/­qdrant
qdrant.tech
www.sadasengine.comsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.datomic.comqdrant.tech/­documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsphinxsearch.com/­docs
DeveloperCognitectQdrantSADAS s.r.l.Sphinx Technologies Inc.
Initial release20192012202120062001
Current release1.0.6735, June 20238.03.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoApache Version 2.0commercial infofree trial version availableOpen Source infoGPL version 2, commercial licence available
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 languageJava, ClojureRustC++C++
Server operating systemshostedAll OS with a Java VMDocker
Linux
macOS
Windows
AIX
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesNumbers, Strings, Geo, Booleanyesno
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 infoKeywords, numberic ranges, geo, full-textyesyes infofull-text index on all search fields
SQL infoSupport of SQLnononoyesSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
Proprietary protocol
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnono
TriggersnoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardinghorizontal partitioningSharding 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 replicasnone infoBut extensive use of caching in the application peersCollection-level replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency, tunable consistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes 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.yes inforecommended only for testing and developmentyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users and rolesnoKey-based authenticationAccess rights for users, groups and roles according to SQL-standardno

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More resources
Amazon DocumentDBDatomicQdrantSadas EngineSphinx
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