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DBMS > Databricks vs. EsgynDB vs. Geode

System Properties Comparison Databricks vs. EsgynDB vs. Geode

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonGeode  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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Websitewww.databricks.comwww.esgyn.cngeode.apache.org
Technical documentationdocs.databricks.comgeode.apache.org/­docs
DeveloperDatabricksEsgynOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.
Initial release201320152002
Current release1.1, February 2017
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses available as Gemfire
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJava
Server operating systemshostedLinuxAll OS with a Java VM infothe JDK (8 or later) is also required
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes
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.yesnono
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query language (OQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Java Client API
Memcached protocol
RESTful HTTP API
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
All JVM based languages
C++
Groovy
Java
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresuser defined functions
Triggersnoyes infoCache Event Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes, on a single node
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights per client and object definable
More information provided by the system vendor
DatabricksEsgynDBGeode
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEsgynDBGeode
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