DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Aurora vs. FatDB vs. MarkLogic vs. Splice Machine

System Properties Comparison Amazon Aurora vs. FatDB vs. MarkLogic vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonFatDB  Xexclude from comparisonMarkLogic  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.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA .NET NoSQL DBMS that can integrate with and extend SQL Server.Operational and transactional Enterprise NoSQL databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.progress.com/­marklogicsplicemachine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.progress.com/­marklogic/­documentationsplicemachine.com/­how-it-works
DeveloperAmazonFatCloudMarkLogic Corp.Splice Machine
Initial release2015201220012014
Current release11.0, December 20223.1, March 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++Java
Server operating systemshostedWindowsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyes
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.yesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesno infoVia inetgration in SQL Serveryes infoSQL92yes
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infovia applicationsyes infovia XQuery or JavaScriptyes infoJava
Triggersyesyes infovia applicationsyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infocan act as a resource manager in an XA/JTA transactionACID
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.yesyes, with Range Indexesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardno infoCan implement custom security layer via applicationsRole-based access control at the document and subdocument levelsAccess rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon AuroraFatDBMarkLogicSplice Machine
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Recent citations in the news

Introducing the Advanced Python Wrapper Driver for Amazon Aurora | Amazon Web Services
11 June 2024, AWS Blog

Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon ...
10 June 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ...
9 February 2024, AWS Blog

Build generative AI applications with Amazon Aurora and Knowledge Bases for Amazon Bedrock | Amazon Web Services
2 February 2024, AWS Blog

provided by Google News

MarkLogic “The NoSQL Database”. In the MarkLogic Query Console, you can… | by Abhay Srivastava | Apr, 2024
22 April 2024, Medium

Database Platform to Simplify Complex Data | Progress Marklogic
7 February 2023, Progress Software

AI can make logistics data as valuable as intelligence or operational data for mission success
17 April 2024, Breaking Defense

Seven Quick Steps to Setting Up MarkLogic Server in Kubernetes
1 February 2024, release.nl

Intelligence for multi-domain warfighters can now be sourced from logistics operations
13 May 2024, Breaking Defense

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Real-time machine learning with Splice Machine's ML Manager
17 April 2019, TechTarget

How To Axe Db2 But Keep Your Code
10 March 2020, Towards Data Science

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here