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DBMS > Apache IoTDB vs. Prometheus vs. ScyllaDB vs. Valentina Server

System Properties Comparison Apache IoTDB vs. Prometheus vs. ScyllaDB vs. Valentina Server

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonPrometheus  Xexclude from comparisonScyllaDB  Xexclude from comparisonValentina Server  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 storeObject-relational database and reports server
Primary database modelTime Series DBMSTime Series DBMSWide column storeRelational DBMS
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score4.75
Rank#68  Overall
#5  Wide column stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websiteiotdb.apache.orgprometheus.iowww.scylladb.comwww.valentina-db.net
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlprometheus.io/­docsdocs.scylladb.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software FoundationScyllaDBParadigma Software
Initial release2018201520151999
Current release1.1.0, April 2023ScyllaDB Open Source 5.4.1, January 20245.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoOpen Source (AGPL), commercial license availablecommercial
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++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
LinuxLinux
OS X
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 possibleno
Secondary indexesyesnoyes infocluster global secondary indicesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statements (CQL)yes
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
ODBC
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
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyesnoyes, Luayes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
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 possible
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
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 integritynononoyes
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 datayesyesyes
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 tablesyes
User concepts infoAccess controlyesnoAccess rights for users can be defined per objectfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBPrometheusScyllaDBValentina Server
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» 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
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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Apache IoTDBPrometheusScyllaDBValentina Server
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