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DBMS > Databricks vs. Geode vs. Google Cloud Datastore vs. Percona Server for MongoDB

System Properties Comparison Databricks vs. Geode vs. Google Cloud Datastore vs. Percona Server for MongoDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPercona Server for MongoDB  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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA drop-in replacement for MongoDB Community Edition with enterprise-grade features.
Primary database modelDocument store
Relational DBMS
Key-value storeDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.60
Rank#246  Overall
#39  Document stores
Websitewww.databricks.comgeode.apache.orgcloud.google.com/­datastorewww.percona.com/­mongodb/­software/­percona-server-for-mongodb
Technical documentationdocs.databricks.comgeode.apache.org/­docscloud.google.com/­datastore/­docsdocs.percona.com/­percona-distribution-for-mongodb
DeveloperDatabricksOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GooglePercona
Initial release2013200220082015
Current release1.1, February 20173.4.10-2.10, November 2017
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoGPL Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, 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.yesnonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (OQL)SQL-like query language (GQL)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
proprietary protocol using JSON
Supported programming languagesPython
R
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsusing Google App EngineJavaScript
Triggersyes infoCache Event ListenersCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate 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.Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infovia In-Memory Engine
User concepts infoAccess controlAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles
More information provided by the system vendor
DatabricksGeodeGoogle Cloud DatastorePercona Server for MongoDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGeodeGoogle Cloud DatastorePercona Server for MongoDB
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