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DBMS > Amazon DocumentDB vs. Google Cloud Bigtable vs. Netezza vs. Sphinx vs. XTDB

System Properties Comparison Amazon DocumentDB vs. Google Cloud Bigtable vs. Netezza vs. Sphinx vs. XTDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSphinx  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceGoogle'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 search engine for searching in data from different sources, e.g. relational databasesA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelDocument storeKey-value store
Wide column store
Relational DBMSSearch engineDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.09
Rank#351  Overall
#47  Document stores
Websiteaws.amazon.com/­documentdbcloud.google.com/­bigtablewww.ibm.com/­products/­netezzasphinxsearch.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­bigtable/­docssphinxsearch.com/­docswww.xtdb.com/­docs
DeveloperGoogleIBMSphinx Technologies Inc.Juxt Ltd.
Initial release20192015200020012019
Current release3.5.1, February 20231.19, September 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Clojure
Server operating systemshostedhostedLinux infoincluded in applianceFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesnoyes, extensible-data-notation format
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 indexesyesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoyesSQL-like query language (SphinxQL)limited SQL, making use of Apache Calcite
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
OLE DB
Proprietary protocolHTTP REST
JDBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Clojure
Java
Server-side scripts infoStored proceduresnonoyesnono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 operationsAtomic single-row operationsACIDnoACID
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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization conceptno

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More resources
Amazon DocumentDBGoogle Cloud BigtableNetezza infoAlso called PureData System for Analytics by IBMSphinxXTDB infoformerly named Crux
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