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DBMS > Databricks vs. Microsoft Azure Table Storage vs. OpenEdge vs. Oracle Berkeley DB vs. Realm

System Properties Comparison Databricks vs. Microsoft Azure Table Storage vs. OpenEdge vs. Oracle Berkeley DB vs. Realm

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonRealm  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.A Wide Column Store for rapid development using massive semi-structured datasetsApplication development environment with integrated database management systemWidely used in-process key-value storeA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelDocument store
Relational DBMS
Wide column storeRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document 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
Score4.04
Rank#77  Overall
#6  Wide column stores
Score3.45
Rank#85  Overall
#46  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Websitewww.databricks.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlrealm.io
Technical documentationdocs.databricks.comdocumentation.progress.com/­output/­ua/­OpenEdge_latestdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlrealm.io/­docs
DeveloperDatabricksMicrosoftProgress Software CorporationOracle infooriginally developed by Sleepycat, which was acquired by OracleRealm, acquired by MongoDB in May 2019
Initial release20132012198419942014
Current releaseOpenEdge 12.2, March 202018.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infocommercial license availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedhostedAIX
HP-UX
Linux
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Android
Backend: server-less
iOS
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesnoyesyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infoclose to SQL 92yes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language).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
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyesnono inforuns within the applications so server-side scripts are unnecessary
Triggersnoyesyes infoonly for the SQL APIyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4nonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesyes infoIn-Memory realm
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesUsers and groupsnoyes
More information provided by the system vendor
DatabricksMicrosoft Azure Table StorageOpenEdgeOracle Berkeley DBRealm
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksMicrosoft Azure Table StorageOpenEdgeOracle Berkeley DBRealm
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