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DBMS > Badger vs. Databricks vs. Microsoft Azure Table Storage vs. SAP SQL Anywhere vs. Spark SQL

System Properties Comparison Badger vs. Databricks vs. Microsoft Azure Table Storage vs. SAP SQL Anywhere vs. Spark SQL

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.The 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 datasetsRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Relational DBMS
Wide column storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score4.25
Rank#79  Overall
#43  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.sap.com/­products/­technology-platform/­sql-anywhere.htmlspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comhelp.sap.com/­docs/­SAP_SQL_Anywherespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsDatabricksMicrosoftSAP infoformerly SybaseApache Software Foundation
Initial release20172013201219922014
Current release17, July 20153.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedhostedAIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.noyesnoyesno
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLnowith Databricks SQLnoyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesGoPython
R
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyes, in C/C++, Java, .Net or Perlno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoDatabase mirroringnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononoyesno
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standardno
More information provided by the system vendor
BadgerDatabricksMicrosoft Azure Table StorageSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
BadgerDatabricksMicrosoft Azure Table StorageSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSpark SQL
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