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DBMS > Hawkular Metrics vs. Hive vs. Prometheus vs. ScyllaDB

System Properties Comparison Hawkular Metrics vs. Hive vs. Prometheus vs. ScyllaDB

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonHive  Xexclude from comparisonPrometheus  Xexclude from comparisonScyllaDB  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.data warehouse software for querying and managing large distributed datasets, built on HadoopOpen-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
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score4.75
Rank#68  Overall
#5  Wide column stores
Websitewww.hawkular.orghive.apache.orgprometheus.iowww.scylladb.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidecwiki.apache.org/­confluence/­display/­Hive/­Homeprometheus.io/­docsdocs.scylladb.com
DeveloperCommunity supported by Red HatApache Software Foundation infoinitially developed by FacebookScyllaDB
Initial release2014201220152015
Current release3.1.3, April 2022ScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open 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

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 languageJavaJavaGoC++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinux
Windows
Linux
Data schemeschema-freeyesyesschema-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 indexesnoyesnoyes infocluster global secondary indices
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoSQL-like DML and DDL statements (CQL)
APIs and other access methodsHTTP RESTJDBC
ODBC
Thrift
RESTful HTTP/JSON APIProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Supported programming languagesGo
Java
Python
Ruby
C++
Java
PHP
Python
.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 proceduresnoyes infouser defined functions and integration of map-reducenoyes, Lua
Triggersyes infovia Hawkular Alertingnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraselectable replication factoryes infoby Federationselectable replication factor infoRepresentation of geographical distribution of servers is possible
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencynoneEventual 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 datanononono 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.nonoyes infoin-memory tables
User concepts infoAccess controlnoAccess rights for users, groups and rolesnoAccess rights for users can be defined per object
More information provided by the system vendor
Hawkular MetricsHivePrometheusScyllaDB
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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