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DBMS > Databricks vs. Geode vs. GridGain vs. Machbase Neo vs. Sphinx

System Properties Comparison Databricks vs. Geode vs. GridGain vs. Machbase Neo vs. Sphinx

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGeode  Xexclude from comparisonGridGain  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonSphinx  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 processesGridGain is an in-memory computing platform, built on Apache IgniteTimeSeries DBMS for AIoT and BigDataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Key-value storeColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.51
Rank#147  Overall
#25  Key-value stores
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score0.07
Rank#348  Overall
#34  Time Series DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comgeode.apache.orgwww.gridgain.commachbase.comsphinxsearch.com
Technical documentationdocs.databricks.comgeode.apache.org/­docswww.gridgain.com/­docs/­index.htmlmachbase.com/­dbmssphinxsearch.com/­docs
DeveloperDatabricksOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GridGain Systems, Inc.MachbaseSphinx Technologies Inc.
Initial release20132002200720132001
Current release1.1, February 2017GridGain 8.5.1V8.0, August 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercial, open sourcecommercial infofree test version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .Net, Python, REST, SQLCC++
Server operating systemshostedAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Solaris
Windows
z/OS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.yesnoyesno
Secondary indexesyesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (OQL)ANSI-99 for query and DML statements, subset of DDLSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyes (compute grid and cache interceptors can be used instead)nono
Triggersyes infoCache Event Listenersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationyes (replicated cache)selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infovolatile and lookup table
User concepts infoAccess controlAccess rights per client and object definableRole-based access control
Security Hooks for custom implementations
simple password-based access controlno
More information provided by the system vendor
DatabricksGeodeGridGainMachbase Neo infoFormer name was InfinifluxSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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