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DBMS > Databricks vs. EsgynDB vs. Hawkular Metrics vs. Microsoft Access vs. Postgres-XL

System Properties Comparison Databricks vs. EsgynDB vs. Hawkular Metrics vs. Microsoft Access vs. Postgres-XL

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPostgres-XL  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 TrafodionHawkular 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.)Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSRelational DBMSRelational 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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitewww.databricks.comwww.esgyn.cnwww.hawkular.orgwww.microsoft.com/­en-us/­microsoft-365/­accesswww.postgres-xl.org
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedeveloper.microsoft.com/­en-us/­accesswww.postgres-xl.org/­documentation
DeveloperDatabricksEsgynCommunity supported by Red HatMicrosoft
Initial release20132015201419922014 infosince 2012, originally named StormDB
Current release1902 (16.0.11328.20222), March 201910 R1, October 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infoBundled with Microsoft OfficeOpen Source infoMozilla public license
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 languageC++, JavaJavaC++C
Server operating systemshostedLinuxLinux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
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.yesnonoyes infoXML type, but no XML query functionality
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLyesnoyes infobut not compliant to any SQL standardyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
HTTP RESTADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetGo
Java
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresnoyes infosince Access 2010 using the ACE-engineuser defined functions
Triggersnoyes infovia Hawkular Alertingyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandranonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersselectable replication factor infobased on Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infobut no files for transaction loggingACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardnono infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksEsgynDBHawkular MetricsMicrosoft AccessPostgres-XL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEsgynDBHawkular MetricsMicrosoft AccessPostgres-XL
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