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DBMS > Blueflood vs. Kinetica vs. MongoDB vs. TDengine

System Properties Comparison Blueflood vs. Kinetica vs. MongoDB vs. TDengine

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonKinetica  Xexclude from comparisonMongoDB  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraFully vectorized database across both GPUs and CPUsOne 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 platform
Primary database modelTime Series DBMSRelational DBMSDocument storeTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial 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 DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score421.65
Rank#5  Overall
#1  Document stores
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteblueflood.iowww.kinetica.comwww.mongodb.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.kinetica.comwww.mongodb.com/­docs/­manualdocs.tdengine.com
DeveloperRackspaceKineticaMongoDB, IncTDEngine, previously Taos Data
Initial release2013201220092019
Current release7.1, August 20216.0.7, June 20233.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen 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 available
Cloud-based only infoOnly available as a cloud servicenonono infoMongoDB available as DBaaS (MongoDB Atlas)no
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C++C
Server operating systemsLinux
OS X
LinuxLinux
OS X
Solaris
Windows
Linux
Windows
Data schemepredefined 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.yes
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsRead-only SQL queries via the MongoDB Atlas SQL InterfaceStandard SQL with extensions for time-series applications
APIs and other access methodsHTTP RESTJDBC
ODBC
RESTful HTTP API
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
JDBC
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
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
Server-side scripts infoStored proceduresnouser defined functionsJavaScriptno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoin MongoDB Atlas onlyyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingSharding 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
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Foreign keys infoReferential integritynoyesno infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by defaultyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlnoAccess rights for users and roles on table levelAccess rights for users and rolesyes
More information provided by the system vendor
BluefloodKineticaMongoDBTDengine
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
TDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» 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
Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» 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
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
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