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DBMS > Amazon DocumentDB vs. Elasticsearch vs. FatDB vs. Google Cloud Spanner

System Properties Comparison Amazon DocumentDB vs. Elasticsearch vs. FatDB vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA .NET NoSQL DBMS that can integrate with and extend SQL Server.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelDocument storeSearch engineDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score128.79
Rank#8  Overall
#1  Search engines
Score2.69
Rank#101  Overall
#51  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearchcloud.google.com/­spanner
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­spanner/­docs
DeveloperElasticFatCloudGoogle
Initial release2019201020122017
Current release8.6, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#
Server operating systemshostedAll OS with a Java VMWindowshosted
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like query languageno infoVia inetgration in SQL Serveryes infoQuery statements complying to ANSI 2011
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesyes infovia applicationsno
Triggersnoyes infoby using the 'percolation' featureyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesselectable replication factorMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop Connectoryesyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonoACID infoStrict serializable isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationno
User concepts infoAccess controlAccess rights for users and rolesno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon DocumentDBElasticsearchFatDBGoogle Cloud Spanner
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Unlock the power of parallel indexing in Amazon DocumentDB
19 June 2024, AWS Blog

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16 May 2024, AWS Blog

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Unlock the power of Amazon DocumentDB text search with real-world use cases
5 March 2024, AWS Blog

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28 March 2024, AWS Blog

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