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DBMS > Datomic vs. InterSystems Caché vs. MongoDB vs. TDengine vs. Vertica

System Properties Comparison Datomic vs. InterSystems Caché vs. MongoDB vs. TDengine vs. Vertica

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMongoDB  Xexclude from comparisonTDengine  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA multi-model DBMS and application serverOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureTime Series DBMS and big data platformCloud 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 modelRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Document storeTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial 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
Relational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score421.65
Rank#5  Overall
#1  Document stores
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.datomic.comwww.intersystems.com/­products/­cachewww.mongodb.comgithub.com/­taosdata/­TDengine
tdengine.com
www.vertica.com
Technical documentationdocs.datomic.comdocs.intersystems.comwww.mongodb.com/­docs/­manualdocs.tdengine.comvertica.com/­documentation
DeveloperCognitectInterSystemsMongoDB, IncTDEngine, previously Taos DataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20121997200920192005
Current release1.0.6735, June 20232018.1.4, May 20206.0.7, June 20233.0, August 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen 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 infoAGPL V3, also commercial editions availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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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Implementation languageJava, ClojureC++CC++
Server operating systemsAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Windows
Linux
Data schemeyesdepending on used data modelschema-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.noyesnono
Secondary indexesyesyesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesRead-only SQL queries via the MongoDB Atlas SQL InterfaceStandard SQL with extensions for time-series applicationsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP API.NET Client API
JDBC
ODBC
RESTful HTTP API
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
JDBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
Java
C#
C++
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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoTransaction FunctionsyesJavaScriptnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersBy using transaction functionsyesyes infoin MongoDB Atlas onlyyes, via alarm monitoringyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.Shardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
yesMulti-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 methodsnonoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Immediate Consistency
Foreign keys infoReferential integritynoyesno infotypically not used, however similar functionality with DBRef possiblenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDMulti-document ACID Transactions with snapshot isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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 developmentyesyes infoIn-memory storage engine introduced with MongoDB version 3.2no
User concepts infoAccess controlnoAccess rights for users, groups and rolesAccess rights for users and rolesyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatomicInterSystems CachéMongoDBTDengineVertica infoOpenText™ Vertica™
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» 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
High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» 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
TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» 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
TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more
TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
Cost-based models and subscription-based models are both available. One license is...
» more
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