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DBMS > Databricks vs. Hawkular Metrics vs. Microsoft Access vs. MonetDB vs. WakandaDB

System Properties Comparison Databricks vs. Hawkular Metrics vs. Microsoft Access vs. MonetDB vs. WakandaDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMonetDB  Xexclude from comparisonWakandaDB  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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A relational database management system that stores data in columnsWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.databricks.comwww.hawkular.orgwww.microsoft.com/­en-us/­microsoft-365/­accesswww.monetdb.orgwakanda.github.io
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedeveloper.microsoft.com/­en-us/­accesswww.monetdb.org/­Documentationwakanda.github.io/­doc
DeveloperDatabricksCommunity supported by Red HatMicrosoftMonetDB BVWakanda SAS
Initial release20132014199220042012
Current release1902 (16.0.11328.20222), March 2019Dec2023 (11.49), December 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoBundled with Microsoft OfficeOpen Source infoMozilla Public License 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++CC++, JavaScript
Server operating systemshostedLinux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infobut not compliant to any SQL standardyes infoSQL 2003 with some extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTADO.NET
DAO
ODBC
OLE DB
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
Go
Java
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infosince Access 2010 using the ACE-engineyes, in SQL, C, Ryes
Triggersyes infovia Hawkular Alertingyes infosince Access 2010 using the ACE-engineyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandranoneSharding via remote tablesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandranonenone infoSource-replica replication available in experimental statusnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infobut no files for transaction loggingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnono infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standardyes
More information provided by the system vendor
DatabricksHawkular MetricsMicrosoft AccessMonetDBWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHawkular MetricsMicrosoft AccessMonetDBWakandaDB
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