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DBMS > Prometheus vs. Quasardb vs. ScyllaDB vs. Spark SQL

System Properties Comparison Prometheus vs. Quasardb vs. ScyllaDB vs. Spark SQL

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Editorial information provided by DB-Engines
NamePrometheus  Xexclude from comparisonQuasardb  Xexclude from comparisonScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source Time Series DBMS and monitoring systemDistributed, high-performance timeseries databaseCassandra and DynamoDB compatible wide column storeSpark SQL is a component on top of 'Spark Core' for structured data processing
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
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score4.08
Rank#76  Overall
#5  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteprometheus.ioquasar.aiwww.scylladb.comspark.apache.org/­sql
Technical documentationprometheus.io/­docsdoc.quasar.ai/­masterdocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperquasardbScyllaDBApache Software Foundation
Initial release2015200920152014
Current release3.14.1, January 2024ScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageGoC++C++Scala
Server operating systemsLinux
Windows
BSD
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateNumeric data onlyyes infointeger and binaryyesyes
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.no infoImport of XML data possiblenonono
Secondary indexesnoyes infowith tagsyes infocluster global secondary indicesno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP/JSON APIHTTP APIProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
ODBC
Supported programming languages.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes, Luano
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby FederationSource-replica replication with selectable replication factorselectable replication factor infoRepresentation of geographical distribution of servers is possiblenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual 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 datanoACIDno infoAtomicity and isolation are supported for single operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes infoin-memory tablesno
User concepts infoAccess controlnoCryptographically strong user authentication and audit trailAccess rights for users can be defined per objectno
More information provided by the system vendor
PrometheusQuasardbScyllaDBSpark SQL
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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PrometheusQuasardbScyllaDBSpark SQL
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