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DBMS > Databricks vs. Dgraph vs. Ehcache vs. Google Cloud Datastore vs. MarkLogic

System Properties Comparison Databricks vs. Dgraph vs. Ehcache vs. Google Cloud Datastore vs. MarkLogic

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDgraph  Xexclude from comparisonEhcache  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMarkLogic  Xexclude from comparison
DescriptionThe 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.Distributed and scalable native Graph DBMSA widely adopted Java cache with tiered storage optionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOperational and transactional Enterprise NoSQL database
Primary database modelDocument store
Relational DBMS
Graph DBMSKey-value storeDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Websitewww.databricks.comdgraph.iowww.ehcache.orgcloud.google.com/­datastorewww.marklogic.com
Technical documentationdocs.databricks.comdgraph.io/­docswww.ehcache.org/­documentationcloud.google.com/­datastore/­docsdocs.marklogic.com
DeveloperDatabricksDgraph Labs, Inc.Terracotta Inc, owned by Software AGGoogleMarkLogic Corp.
Initial release20132016200920082001
Current release3.10.0, March 202211.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC++
Server operating systemshostedLinux
OS X
Windows
All OS with a Java VMhostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-freeschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.yesnononoyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnonoSQL-like query language (GQL)yes infoSQL92
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
JCachegRPC (using protocol buffers) API
RESTful HTTP/JSON API
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
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonousing Google App Engineyes infovia XQuery or JavaScript
Triggersnoyes infoCache Event ListenersCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesyesSharding infoby using Terracotta ServerShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSynchronous replication via Raftyes infoby using Terracotta ServerMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes infosupports JTA and can work as an XA resourceACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes, with Range Indexes
User concepts infoAccess controlno infoPlanned for future releasesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levels
More information provided by the system vendor
DatabricksDgraphEhcacheGoogle Cloud DatastoreMarkLogic
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDgraphEhcacheGoogle Cloud DatastoreMarkLogic
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