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DBMS > Databricks vs. Hawkular Metrics vs. Heroic vs. ScyllaDB

System Properties Comparison Databricks vs. Hawkular Metrics vs. Heroic vs. ScyllaDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHeroic  Xexclude from comparisonScyllaDB  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchCassandra and DynamoDB compatible wide column store
Primary database modelDocument store
Relational DBMS
Time Series DBMSTime Series DBMSWide column store
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.75
Rank#68  Overall
#5  Wide column stores
Websitewww.databricks.comwww.hawkular.orggithub.com/­spotify/­heroicwww.scylladb.com
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidespotify.github.io/­heroicdocs.scylladb.com
DeveloperDatabricksCommunity supported by Red HatSpotifyScyllaDB
Initial release2013201420142015
Current releaseScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoOpen Source (AGPL), commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 languageJavaJavaC++
Server operating systemshostedLinux
OS X
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes
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.yesnonono
Secondary indexesyesnoyes infovia Elasticsearchyes infocluster global secondary indices
SQL infoSupport of SQLwith Databricks SQLnonoSQL-like DML and DDL statements (CQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTHQL (Heroic Query Language, a JSON-based language)
HTTP API
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Supported programming languagesPython
R
Scala
Go
Java
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 proceduresuser defined functions and aggregatesnonoyes, Lua
Triggersyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandrayesselectable replication factor infoRepresentation of geographical distribution of servers is possible
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Eventual 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 dataACIDnonono 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.nononoyes infoin-memory tables
User concepts infoAccess controlnoAccess rights for users can be defined per object
More information provided by the system vendor
DatabricksHawkular MetricsHeroicScyllaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
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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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DatabricksHawkular MetricsHeroicScyllaDB
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