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DBMS > Amazon DocumentDB vs. Apache Pinot vs. GigaSpaces vs. IRONdb vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Apache Pinot vs. GigaSpaces vs. IRONdb vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Pinot  Xexclude from comparisonGigaSpaces  Xexclude from comparisonIRONdb  Xexclude from comparisonSphinx  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSSearch engine
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbpinot.apache.orgwww.gigaspaces.comwww.circonus.com/solutions/time-series-database/sphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.pinot.apache.orgdocs.gigaspaces.com/­latest/­landing.htmldocs.circonus.com/irondb/category/getting-startedsphinxsearch.com/­docs
DeveloperApache Software Foundation and contributorsGigaspaces TechnologiesCirconus LLC.Sphinx Technologies Inc.
Initial release20192015200020172001
Current release1.0.0, September 202315.5, September 2020V0.10.20, January 20183.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availablecommercialOpen 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 languageJavaJava, C++, .NetC and C++C++
Server operating systemshostedAll OS with a Java JDK11 or higherLinux
macOS
Solaris
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infotext, numeric, histogramsno
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-like query languageSQL-99 for query and DML statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP APIProprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Go
Java
Python
.Net
C++
Java
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesyes, in Luano
Triggersnoyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningShardingAutomatic, metric affinity per nodeSharding 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
configurable replication factor, datacenter awarenone
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 per node, eventual consistency across nodes
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 operationsACIDnono
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.yesno
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlnono

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More resources
Amazon DocumentDBApache PinotGigaSpacesIRONdbSphinx
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