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DBMS > FatDB vs. ScyllaDB vs. Spark SQL vs. Speedb

System Properties Comparison FatDB vs. ScyllaDB vs. Spark SQL vs. Speedb

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSpeedb  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cassandra and DynamoDB compatible wide column storeSpark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB
Primary database modelDocument store
Key-value store
Wide column storeRelational DBMSKey-value store
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.75
Rank#68  Overall
#5  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.21
Rank#315  Overall
#45  Key-value stores
Websitewww.scylladb.comspark.apache.org/­sqlwww.speedb.io
Technical documentationdocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudScyllaDBApache Software FoundationSpeedb
Initial release2012201520142020
Current releaseScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache 2.0Open Source infoApache Version 2.0; 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 languageC#C++ScalaC++
Server operating systemsWindowsLinuxLinux
OS X
Windows
Linux
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nonono
Secondary indexesyesyes infocluster global secondary indicesnono
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statementsno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
ODBC
Supported programming languagesC#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
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresyes infovia applicationsyes, Luanono
Triggersyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infoRepresentation of geographical distribution of servers is possiblenoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual 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 datanono infoAtomicity and isolation are supported for single operationsnoyes
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.yes infoin-memory tablesnoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users can be defined per objectnono
More information provided by the system vendor
FatDBScyllaDBSpark SQLSpeedb
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Speedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Speedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» 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
Open source - Speedb OSS is released under an Apache license and can be found on...
» more

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