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DBMS > Databricks vs. Hawkular Metrics vs. Immudb

System Properties Comparison Databricks vs. Hawkular Metrics vs. Immudb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonImmudb  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.An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.
Primary database modelDocument store
Relational DBMS
Time Series DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.24
Rank#295  Overall
#42  Key-value stores
Websitewww.databricks.comwww.hawkular.orggithub.com/­codenotary/­immudb
immudb.io
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.immudb.io
DeveloperDatabricksCommunity supported by Red HatCodenotary
Initial release201320142020
Current release1.2.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemshostedLinux
OS X
Windows
BSD
Linux
macOS
Solaris
Windows
z/OS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyes
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 indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTgRPC protocol
PostgreSQL wire protocol
Supported programming languagesPython
R
Scala
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
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 integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlno
More information provided by the system vendor
DatabricksHawkular MetricsImmudb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHawkular MetricsImmudb
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