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DBMS > Datomic vs. Prometheus vs. ScyllaDB vs. Solr

System Properties Comparison Datomic vs. Prometheus vs. ScyllaDB vs. Solr

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonPrometheus  Xexclude from comparisonScyllaDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOpen-source Time Series DBMS and monitoring systemCassandra and DynamoDB compatible wide column storeA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSTime Series DBMSWide column storeSearch engine
Secondary database modelsKey-value storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Score5.27
Rank#67  Overall
#5  Wide column stores
Score44.28
Rank#24  Overall
#3  Search engines
Websitewww.datomic.comprometheus.iowww.scylladb.comsolr.apache.org
Technical documentationdocs.datomic.comprometheus.io/­docsdocs.scylladb.comsolr.apache.org/­resources.html
DeveloperCognitectScyllaDBApache Software Foundation
Initial release2012201520152006
Current release1.0.6735, June 2023ScyllaDB Open Source 5.4.1, January 20249.5.0, February 2024
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache Version 2
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 languageJava, ClojureGoC++Java
Server operating systemsAll OS with a Java VMLinux
Windows
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes infosupports customizable data types and automatic typing
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 possiblenoyes
Secondary indexesyesnoyes infocluster global secondary indicesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoSQL-like DML and DDL statements (CQL)Solr Parallel SQL Interface
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Java API
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
.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
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes, LuaJava plugins
TriggersBy using transaction functionsnonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoby Federationselectable replication factor infoRepresentation of geographical distribution of servers is possibleyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoAtomicity and isolation are supported for single operationsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyes infoin-memory tablesyes
User concepts infoAccess controlnonoAccess rights for users can be defined per objectyes
More information provided by the system vendor
DatomicPrometheusScyllaDBSolr
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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