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DBMS > Apache IoTDB vs. Prometheus vs. ScyllaDB vs. TDengine

System Properties Comparison Apache IoTDB vs. Prometheus vs. ScyllaDB vs. TDengine

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonPrometheus  Xexclude from comparisonScyllaDB  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkOpen-source Time Series DBMS and monitoring systemCassandra and DynamoDB compatible wide column storeTime Series DBMS and big data platform
Primary database modelTime Series DBMSTime Series DBMSWide column storeTime Series DBMS
Secondary database modelsKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score4.08
Rank#76  Overall
#5  Wide column stores
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Websiteiotdb.apache.orgprometheus.iowww.scylladb.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlprometheus.io/­docsdocs.scylladb.comdocs.tdengine.com
DeveloperApache Software FoundationScyllaDBTDEngine, previously Taos Data
Initial release2018201520152019
Current release1.1.0, April 2023ScyllaDB Open Source 5.4.1, January 20243.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoOpen Source (AGPL), commercial license availableOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageJavaGoC++C
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
LinuxLinux
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes
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 infoImport of XML data possiblenono
Secondary indexesyesnoyes infocluster global secondary indicesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statements (CQL)Standard SQL with extensions for time-series applications
APIs and other access methodsJDBC
Native API
RESTful HTTP/JSON APIProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyesnoyes, Luano
Triggersyesnonoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoby Federationselectable replication factor infoRepresentation of geographical distribution of servers is possibleyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infoAtomicity and isolation are supported for single operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoin-memory tables
User concepts infoAccess controlyesnoAccess rights for users can be defined per objectyes
More information provided by the system vendor
Apache IoTDBPrometheusScyllaDBTDengine
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more
TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
Apache IoTDBPrometheusScyllaDBTDengine
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