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DBMS > Amazon DocumentDB vs. Cubrid vs. Google BigQuery vs. Sphinx vs. Typesense

System Properties Comparison Amazon DocumentDB vs. Cubrid vs. Google BigQuery vs. Sphinx vs. Typesense

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCubrid  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonSphinx  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPLarge scale data warehouse service with append-only tablesOpen source search engine for searching in data from different sources, e.g. relational databasesA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelDocument storeRelational DBMSRelational DBMSSearch engineSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.76
Rank#219  Overall
#14  Search engines
Websiteaws.amazon.com/­documentdbcubrid.com (korean)
cubrid.org (english)
cloud.google.com/­bigquerysphinxsearch.comtypesense.org
Technical documentationaws.amazon.com/­documentdb/­resourcescubrid.org/­manualscloud.google.com/­bigquery/­docssphinxsearch.com/­docstypesense.org/­docs
DeveloperCUBRID Corporation, CUBRID FoundationGoogleSphinx Technologies Inc.
Initial release20192008201020012015
Current release11.0, January 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaC++C++
Server operating systemshostedLinux
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonono
Secondary indexesyesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyesyesSQL-like query language (SphinxQL)no
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
OLE DB
RESTful HTTP/JSON APIProprietary protocolRESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresnoJava Stored Proceduresuser defined functions infoin JavaScriptnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneSharding 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 replicasSource-replica replicationnoneMulti-source replication using RAFT
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDno infoSince BigQuery is designed for querying datanono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nonoyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)no

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