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

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTitan  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
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 processingTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument store
Key-value store
Wide column storeRelational DBMSGraph DBMS
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
Websitewww.scylladb.comspark.apache.org/­sqlgithub.com/­thinkaurelius/­titan
Technical documentationdocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlgithub.com/­thinkaurelius/­titan/­wiki
DeveloperFatCloudScyllaDBApache Software FoundationAurelius, owned by DataStax
Initial release2012201520142012
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 license, version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
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 languageC#C++ScalaJava
Server operating systemsWindowsLinuxLinux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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
Secondary indexesyesyes infocluster global secondary indicesnoyes
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
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
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
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infovia applicationsyes, Luanoyes
Triggersyes infovia applicationsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Coreyes infovia pluggable storage backends
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 methodsyesnoyes infovia Faunus, a graph analytics engine
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
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoin-memory tablesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users can be defined per objectnoUser authentification and security via Rexster Graph Server
More information provided by the system vendor
FatDBScyllaDBSpark SQLTitan
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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