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DBMS > Amazon DocumentDB vs. GigaSpaces vs. Google Cloud Bigtable vs. Netezza vs. SiriDB

System Properties Comparison Amazon DocumentDB vs. GigaSpaces vs. Google Cloud Bigtable vs. Netezza vs. SiriDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSiriDB  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 TransactionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Data warehouse and analytics appliance part of IBM PureSystemsOpen Source Time Series DBMS
Primary database modelDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Key-value store
Wide column store
Relational DBMSTime Series DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websiteaws.amazon.com/­documentdbwww.gigaspaces.comcloud.google.com/­bigtablewww.ibm.com/­products/­netezzasiridb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­bigtable/­docsdocs.siridb.com
DeveloperGigaspaces TechnologiesGoogleIBMCesbit
Initial release20192000201520002017
Current release15.5, September 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC
Server operating systemshostedLinux
macOS
Solaris
Windows
hostedLinux infoincluded in applianceLinux
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes infoNumeric data
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 metadatanono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsnoyesno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
OLE DB
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C++
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyesnoyesno
Triggersnoyes, event driven architecturenonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding
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
Internal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes
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 executorsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
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 operationsACIDAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization conceptsimple rights management via user accounts

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More resources
Amazon DocumentDBGigaSpacesGoogle Cloud BigtableNetezza infoAlso called PureData System for Analytics by IBMSiriDB
Recent citations in the news

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces Amazon DocumentDB I/O-Optimized
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U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
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