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DBMS > Amazon Neptune vs. Databricks vs. FatDB vs. Geode

System Properties Comparison Amazon Neptune vs. Databricks vs. FatDB vs. Geode

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonGeode  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Document store
Key-value store
Key-value store
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
Score1.86
Rank#134  Overall
#24  Key-value stores
Websiteaws.amazon.com/­neptunewww.databricks.comgeode.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.databricks.comgeode.apache.org/­docs
DeveloperAmazonDatabricksFatCloudOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.
Initial release2017201320122002
Current release1.1, February 2017
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2; commercial licenses available as Gemfire
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#Java
Server operating systemshostedhostedWindowsAll OS with a Java VM infothe JDK (8 or later) is also required
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
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.noyesno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnowith Databricks SQLno infoVia inetgration in SQL ServerSQL-like query language (OQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java Client API
Memcached protocol
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Python
R
Scala
C#.Net
All JVM based languages
C++
Groovy
Java
Scala
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes infovia applicationsuser defined functions
Triggersnoyes infovia applicationsyes infoCache Event Listeners
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
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.yesselectable replication factorMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoyes, on a single node
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)no infoCan implement custom security layer via applicationsAccess rights per client and object definable
More information provided by the system vendor
Amazon NeptuneDatabricksFatDBGeode
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon NeptuneDatabricksFatDBGeode
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