DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > 4D vs. AlaSQL vs. Amazon Neptune vs. Atos Standard Common Repository vs. Splice Machine

System Properties Comparison 4D vs. AlaSQL vs. Amazon Neptune vs. Atos Standard Common Repository vs. Splice Machine

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAlaSQL  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonSplice Machine  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionApplication development environment with integrated database management systemJavaScript DBMS libraryFast, reliable graph database built for the cloudHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument store
Relational DBMS
Graph DBMS
RDF store
Document store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.4d.comalasql.orgaws.amazon.com/­neptuneatos.net/en/convergence-creators/portfolio/standard-common-repositorysplicemachine.com
Technical documentationdeveloper.4d.comgithub.com/­AlaSQL/­alasqlaws.amazon.com/­neptune/­developer-resourcessplicemachine.com/­how-it-works
Developer4D, IncAndrey Gershun & Mathias R. WulffAmazonAtos Convergence CreatorsSplice Machine
Initial release19842014201720162014
Current releasev20, April 202317033.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoMIT-LicensecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptJavaJava
Server operating systemsOS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)hostedLinuxLinux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeSchema and schema-less with LDAP viewsyes
Typing infopredefined data types such as float or dateyesnoyesoptionalyes
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.yesnonoyes
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLyes infoclose to SQL 92Close to SQL99, but no user access control, stored procedures and host language bindings.nonoyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JavaScript APIOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
LDAPJDBC
Native Spark Datasource
ODBC
Supported programming languages4D proprietary IDE
PHP
JavaScriptC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages with LDAP bindingsC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesnononoyes infoJava
Triggersyesyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneSharding infocell divisionShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesyes infoRelationships in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infoonly for local storage and DOM-storageACIDAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyes infowith encyption-at-restyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlUsers and groupsnoAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)LDAP bind authenticationAccess 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
4D infoformer name: 4th DimensionAlaSQLAmazon NeptuneAtos Standard Common RepositorySplice Machine
DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

HarperDB - How and Why We Built It From The Ground Up on NodeJS
28 February 2021, hackernoon.com

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

Exploring new features of Apache TinkerPop 3.7.x in Amazon Neptune | Amazon Web Services
7 June 2024, AWS Blog

Building NHM London's Planetary Knowledge Base with Amazon Neptune and the Registry of Open Data on AWS ...
5 June 2024, AWS Blog

AWS Weekly Roundup: LlamaIndex support for Amazon Neptune, force AWS CloudFormation stack deletion, and more ...
27 May 2024, AWS Blog

AWS announces Amazon Neptune I/O-Optimized
22 February 2024, AWS Blog

Amazon Neptune Analytics is now available in the AWS Europe (London) Region
14 March 2024, AWS Blog

provided by Google News

Infographic: What makes a Mobile Operator's setup future proof?
10 February 2024, Atos

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

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

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

ETL: The Silent Killer of Big Data Projects
23 July 2015, insideBIGDATA

provided by Google News



Share this page

Featured Products

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

Milvus logo

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

Present your product here