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DBMS > Databricks vs. ScyllaDB vs. Sqrrl vs. Valentina Server

System Properties Comparison Databricks vs. ScyllaDB vs. Sqrrl vs. Valentina Server

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonScyllaDB  Xexclude from comparisonSqrrl  Xexclude from comparisonValentina Server  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
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.Cassandra and DynamoDB compatible wide column storeAdaptable, secure NoSQL built on Apache AccumuloObject-relational database and reports server
Primary database modelDocument store
Relational DBMS
Wide column storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
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
Score4.75
Rank#68  Overall
#5  Wide column stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.databricks.comwww.scylladb.comsqrrl.comwww.valentina-db.net
Technical documentationdocs.databricks.comdocs.scylladb.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperDatabricksScyllaDBAmazon infooriginally Sqrrl Data, Inc.Paradigma Software
Initial release2013201520121999
Current releaseScyllaDB Open Source 5.4.1, January 20245.7.5
License infoCommercial or Open SourcecommercialOpen Source infoOpen Source (AGPL), commercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 languageC++Java
Server operating systemshostedLinuxLinuxLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
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.yesno
Secondary indexesyesyes infocluster global secondary indicesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statements (CQL)noyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ODBC
Supported programming languagesPython
R
Scala
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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes, Luanoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infoRepresentation of geographical distribution of servers is possibleselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoAtomicity and isolation are supported for single operationsAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes infoin-memory tablesyes
User concepts infoAccess controlAccess rights for users can be defined per objectCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksScyllaDBSqrrlValentina Server
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
ScyllaDB 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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DatabricksScyllaDBSqrrlValentina Server
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