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DBMS > Databricks vs. GigaSpaces vs. Oracle Berkeley DB vs. Sadas Engine

System Properties Comparison Databricks vs. GigaSpaces vs. Oracle Berkeley DB vs. Sadas Engine

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSadas Engine  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.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsWidely used in-process key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.03
Rank#379  Overall
#156  Relational DBMS
Websitewww.databricks.comwww.gigaspaces.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.sadasengine.com
Technical documentationdocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmldocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperDatabricksGigaspaces TechnologiesOracle infooriginally developed by Sleepycat, which was acquired by OracleSADAS s.r.l.
Initial release2013200019942006
Current release15.5, September 202018.1.40, May 20208.0
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infocommercial license availablecommercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemshostedLinux
macOS
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
AIX
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.yesno infoXML can be used for describing objects metadatayes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-99 for query and DML statementsyes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
C++
Java
Python
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnono
Triggersyes, event driven architectureyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyesyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlRole-based access controlnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksGigaSpacesOracle Berkeley DBSadas Engine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGigaSpacesOracle Berkeley DBSadas Engine
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