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DBMS > Amazon CloudSearch vs. Datomic vs. MongoDB vs. TypeDB vs. Vertica

System Properties Comparison Amazon CloudSearch vs. Datomic vs. MongoDB vs. TypeDB vs. Vertica

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonDatomic  Xexclude from comparisonMongoDB  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query languageCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelSearch engineRelational DBMSDocument storeGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Relational DBMS infoColumn oriented
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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.87
Rank#140  Overall
#12  Search engines
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score423.96
Rank#5  Overall
#1  Document stores
Score0.81
Rank#217  Overall
#19  Graph DBMS
#99  Relational DBMS
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websiteaws.amazon.com/­cloudsearchwww.datomic.comwww.mongodb.comtypedb.comwww.vertica.com
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.datomic.comwww.mongodb.com/­docs/­manualtypedb.com/­docsvertica.com/­documentation
DeveloperAmazonCognitectMongoDB, IncVaticleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122012200920162005
Current release1.0.6735, June 20236.0.7, June 20232.26.3, January 202412.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoGPL Version 3, commercial licenses availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnono infoMongoDB available as DBaaS (MongoDB Atlas)nono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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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 languageJava, ClojureC++JavaC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesschema-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.yesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyesyes
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 indexesyes infoall search fields are automatically indexedyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoRead-only SQL queries via the MongoDB Atlas SQL InterfacenoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP APIRESTful HTTP APIGraphQL
HTTP REST
Prisma
proprietary protocol using JSON
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
Actionscript 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
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoTransaction FunctionsJavaScriptnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoBy using transaction functionsyes infoin MongoDB Atlas onlynoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requirednone infoBut extensive use of caching in the application peersSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.Sharding infoby using Cassandrahorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSnone infoBut extensive use of caching in the application peersMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
Multi-source replication infoby using CassandraMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infoby using Apache Kafka and Apache Zookeeperno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infotypically not used, however similar functionality with DBRef possibleno infosubstituted by the relationship featureyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDMulti-document ACID Transactions with snapshot isolationACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infooptional, enabled by defaultyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes infoIn-memory storage engine introduced with MongoDB version 3.2nono
User concepts infoAccess controlauthentication via encrypted signaturesnoAccess rights for users and rolesyes infoat REST API level; other APIs in progressfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon CloudSearchDatomicMongoDBTypeDB infoformerly named GraknVertica infoOpenText™ Vertica™
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesBuilt around the flexible document data model and unified API, MongoDB is a developer...
» more
TypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Life sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» 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
Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
Amazon CloudSearchDatomicMongoDBTypeDB infoformerly named GraknVertica infoOpenText™ Vertica™
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