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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonOushuDB  Xexclude from comparisonPrometheus  Xexclude from comparisonScyllaDB  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 FlinkA data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningOpen-source Time Series DBMS and monitoring systemCassandra and DynamoDB compatible wide column store
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSWide column store
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.10
Rank#355  Overall
#154  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score4.08
Rank#76  Overall
#5  Wide column stores
Websiteiotdb.apache.orgwww.oushu.com/­product/­oushuDBprometheus.iowww.scylladb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.oushu.com/­documentationprometheus.io/­docsdocs.scylladb.com
DeveloperApache Software FoundationOushuScyllaDB
Initial release201820152015
Current release1.1.0, April 20234.0.1, August 2020ScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoOpen Source (AGPL), commercial license 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++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
Windows
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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 indexesyesyesnoyes infocluster global secondary indices
SQL infoSupport of SQLSQL-like query languageFull-featured ANSI SQL supportnoSQL-like DML and DDL statements (CQL)
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP/JSON APIProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
.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
Server-side scripts infoStored proceduresyesyesnoyes, Lua
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yesShardingSharding
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 SparkHadoop integrationnono
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono 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 controlyesKerberos, SSL and role based accessnoAccess rights for users can be defined per object
More information provided by the system vendor
Apache IoTDBOushuDBPrometheusScyllaDB
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 IoTDBOushuDBPrometheusScyllaDB
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