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DBMS > BigObject vs. MongoDB vs. Pinecone

System Properties Comparison BigObject vs. MongoDB vs. Pinecone

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonMongoDB  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureA managed, cloud-native vector database
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument storeVector DBMS
Secondary database modelsSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Vector DBMS infocurrently available in the MongoDB Atlas cloud service only
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#342  Overall
#150  Relational DBMS
Score423.96
Rank#5  Overall
#1  Document stores
Score3.29
Rank#94  Overall
#2  Vector DBMS
Websitebigobject.iowww.mongodb.comwww.pinecone.io
Technical documentationdocs.bigobject.iowww.mongodb.com/­docs/­manualdocs.pinecone.io/­docs/­overview
DeveloperBigObject, Inc.MongoDB, IncPinecone Systems, Inc
Initial release201520092019
Current release6.0.7, June 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.commercial
Cloud-based only infoOnly available as a cloud servicenono infoMongoDB available as DBaaS (MongoDB Atlas)yes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
Implementation languageC++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Solaris
Windows
hosted
Data schemeyesschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialString, 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.nono
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsRead-only SQL queries via the MongoDB Atlas SQL Interfaceno
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
RESTful HTTP API
Supported programming languagesActionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
Python
Server-side scripts infoStored proceduresLuaJavaScript
Triggersnoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesno infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes
Durability infoSupport for making data persistentyesyes infooptional, enabled by defaultyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoIn-memory storage engine introduced with MongoDB version 3.2no
User concepts infoAccess controlnoAccess rights for users and roles
More information provided by the system vendor
BigObjectMongoDBPinecone
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Competitive advantagesBuilt around the flexible document data model and unified API, MongoDB is a developer...
» more
Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metricsHundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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More resources
BigObjectMongoDBPinecone
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Conferences, events and webinars

Intro to MongoDB
Webinar, 11am ET, 1 May 2024

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