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DBMS > Amazon DocumentDB vs. GigaSpaces vs. QuestDB vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. GigaSpaces vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSSearch engine
Secondary database modelsGraph DBMS
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.80
Rank#148  Overall
#25  Document stores
Score1.05
Rank#191  Overall
#31  Document stores
#6  Object oriented DBMS
Score2.69
Rank#115  Overall
#8  Time Series DBMS
Score6.06
Rank#61  Overall
#6  Search engines
Websiteaws.amazon.com/­documentdbwww.gigaspaces.comquestdb.iosphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.gigaspaces.com/­latest/­landing.htmlquestdb.io/­docssphinxsearch.com/­docs
DeveloperGigaspaces TechnologiesQuestDB Technology IncSphinx Technologies Inc.
Initial release2019200020142001
Current release15.5, September 20203.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJava (Zero-GC), C++, RustC++
Server operating systemshostedLinux
macOS
Solaris
Windows
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyesno
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.nono infoXML can be used for describing objects metadatano
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C++
Java
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning (by timestamps)Sharding 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 replicasMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 infothrough memory mapped files
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlno
More information provided by the system vendor
Amazon DocumentDBGigaSpacesQuestDBSphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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