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DBMS > Amazon DocumentDB vs. Elasticsearch vs. Pinecone

System Properties Comparison Amazon DocumentDB vs. Elasticsearch vs. Pinecone

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonPinecone  Xexclude from comparison
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 managed, cloud-native vector database
Primary database modelDocument storeSearch engine
Vector DBMS
Vector DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#125  Overall
#22  Document stores
Score134.92
Rank#8  Overall
#1  Search engines
#1  Vector DBMS
Score3.20
Rank#81  Overall
#5  Vector DBMS
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearchwww.pinecone.io
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.pinecone.io/­docs/­overview
DeveloperElasticPinecone Systems, Inc
Initial release201920102019
Current release8.6, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic Licensecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedAll OS with a Java VMhosted
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistent
Typing infopredefined data types such as float or dateyesyesString, Number, Boolean
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 indexed
SQL infoSupport of SQLnoSQL-like query languageno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Python
Server-side scripts infoStored proceduresnoyes
Triggersnoyes infoby using the 'percolation' feature
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop Connectorno
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, all
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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 roles

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More resources
Amazon DocumentDBElasticsearchPinecone
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Recent citations in the news

Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service is now available
16 May 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0
15 April 2024, AWS Blog

Unlock the power of parallel indexing in Amazon DocumentDB
19 June 2024, AWS Blog

Optimizing costs on Amazon DocumentDB using event-driven architecture and the AWS EventBridge Terraform module
23 August 2024, AWS Blog

Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot
20 May 2024, AWS Blog

provided by Google News

Vespa.ai Announces Significant Performance Gains Over Elasticsearch in New Benchmark
16 January 2025, Business Wire

Amazon OpenSearch Service announces Standard and Extended Support dates for Elasticsearch and OpenSearch versions
7 November 2024, AWS Blog

Elasticsearch Was Great, But Vector Databases Are the Future
18 November 2024, The New Stack

Elasticsearch will be open source again as CTO declares changed landscape
2 September 2024, DevClass

The Elasticsearch cloud now subject to open-source licence
3 September 2024, TechHQ

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Pinecone expands vector database with cascading retrieval, boosting enterprise AI accuracy by up to 48%
2 December 2024, VentureBeat

Pinecone integrates AI inferencing with vector database
2 December 2024, Blocks and Files

First-of-its-kind Pinecone Knowledge Platform to Power Best-in-class Retrieval for Customers
3 December 2024, PR Newswire

Pinecone launches serverless vector database on Azure, GCP
27 August 2024, TechTarget

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

provided by Google News



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