DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Neptune vs. Databricks vs. Infobright vs. Yanza

System Properties Comparison Amazon Neptune vs. Databricks vs. Infobright vs. Yanza

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatabricks  Xexclude from comparisonInfobright  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, reliable graph database built for the cloudThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendTime Series DBMS for IoT Applications
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.02
Rank#192  Overall
#90  Relational DBMS
Websiteaws.amazon.com/­neptunewww.databricks.comignitetech.com/­softwarelibrary/­infobrightdbyanza.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.databricks.com
DeveloperAmazonDatabricksIgnite Technologies Inc.; formerly InfoBright Inc.Yanza
Initial release2017201320052015
License infoCommercial or Open Sourcecommercialcommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC
Server operating systemshostedhostedLinux
Windows
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.noyesnono
Secondary indexesnoyesno infoKnowledge Grid Technology used insteadno
SQL infoSupport of SQLnowith Databricks SQLyesno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Python
R
Scala
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
any language that supports HTTP calls
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnono
Triggersnonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesnonenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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.yesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesno
More information provided by the system vendor
Amazon NeptuneDatabricksInfobrightYanza
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

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 NeptuneDatabricksInfobrightYanza
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the 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

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune | Amazon Web Services
3 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

provided by Google News

Infoworks streamlines Hadoop to Databricks migrations with Unity Catalog integration
6 June 2024, PR Newswire

Databricks enhances data lakehouse abilities with the purchase of data optimization startup, Tabular - The National
8 June 2024, The National

Exclusive | Databricks to Buy Data-Management Startup Tabular in Bid for AI Clients
4 June 2024, The Wall Street Journal

Databricks acquires Tabular to build a common data lakehouse standard
4 June 2024, TechCrunch

Databricks acquires data optimization startup Tabular in fresh challenge to Snowflake
4 June 2024, CNBC

provided by Google News



Share this page

Featured Products

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

Neo4j logo

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

Milvus logo

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

Present your product here