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DBMS > Badger vs. Databricks vs. Hawkular Metrics vs. Vertica

System Properties Comparison Badger vs. Databricks vs. Hawkular Metrics vs. Vertica

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonVertica infoOpenText™ Vertica™  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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelKey-value storeDocument store
Relational DBMS
Time Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series 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
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comwww.hawkular.orgwww.vertica.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidevertica.com/­documentation
DeveloperDGraph LabsDatabricksCommunity supported by Red HatOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2017201320142005
Current release12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenoyesyes
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.noyesnono
Secondary indexesnoyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnowith Databricks SQLnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGoPython
R
Scala
Go
Java
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infovia Hawkular Alertingyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on Cassandrahorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesselectable replication factor infobased on CassandraMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BadgerDatabricksHawkular MetricsVertica infoOpenText™ Vertica™
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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BadgerDatabricksHawkular MetricsVertica infoOpenText™ Vertica™
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