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DBMS > Amazon DocumentDB vs. FatDB vs. ScyllaDB vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. FatDB vs. ScyllaDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFatDB  Xexclude from comparisonScyllaDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cassandra and DynamoDB compatible wide column storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeDocument store
Key-value store
Wide column storeRelational DBMS
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score4.15
Rank#69  Overall
#5  Wide column stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.scylladb.comsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.scylladb.comsplicemachine.com/­how-it-works
DeveloperFatCloudScyllaDBSplice Machine
Initial release2019201220152014
Current releaseScyllaDB Open Source 6.0.2, July 20243.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoAGPL 3.0, 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 languageC#C++Java
Server operating systemshostedWindowsLinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
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 indexesyesyesyes infocluster global secondary indicesyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like DML and DDL statements (CQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible).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
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyes, Luayes infoJava
Triggersnoyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factorselectable replication factor infoRepresentation of geographical distribution of servers is possibleMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnono infoAtomicity and isolation are supported for single operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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 tablesyes
User concepts infoAccess controlAccess rights for users and rolesno infoCan implement custom security layer via applicationsAccess rights for users can be defined per objectAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Amazon DocumentDBFatDBScyllaDBSplice Machine
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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More resources
Amazon DocumentDBFatDBScyllaDBSplice Machine
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