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DBMS > Amazon Neptune vs. Databricks vs. Datomic vs. OpenEdge

System Properties Comparison Amazon Neptune vs. Databricks vs. Datomic vs. OpenEdge

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonOpenEdge  Xexclude from comparison
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.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityApplication development environment with integrated database management system
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.51
Rank#86  Overall
#46  Relational DBMS
Websiteaws.amazon.com/­neptunewww.databricks.comwww.datomic.comwww.progress.com/­openedge
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.databricks.comdocs.datomic.comdocumentation.progress.com/­output/­ua/­OpenEdge_latest
DeveloperAmazonDatabricksCognitectProgress Software Corporation
Initial release2017201320121984
Current release1.0.6735, June 2023OpenEdge 12.2, March 2020
License infoCommercial or Open Sourcecommercialcommercialcommercial infolimited edition freecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, Clojure
Server operating systemshostedhostedAll OS with a Java VMAIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesnoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnowith Databricks SQLnoyes infoclose to SQL 92
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Python
R
Scala
Clojure
Java
Progress proprietary ABL (Advanced Business Language)
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes infoTransaction Functionsyes
TriggersnoBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peershorizontal partitioning infosince Version 11.4
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.yesnone infoBut extensive use of caching in the application peersSource-replica replication
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 graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noUsers and groups
More information provided by the system vendor
Amazon NeptuneDatabricksDatomicOpenEdge
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon NeptuneDatabricksDatomicOpenEdge
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