DB-EnginesextremeDB - Data management wherever you need itEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

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

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

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonHawkular Metrics  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 widely adopted Java cache with tiered storage optionsHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelKey-value storeDocument store
Relational DBMS
Key-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#328  Overall
#48  Key-value stores
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score4.79
Rank#66  Overall
#8  Key-value stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comwww.ehcache.orgwww.hawkular.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comwww.ehcache.org/­documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperDGraph LabsDatabricksTerracotta Inc, owned by Software AGCommunity supported by Red Hat
Initial release2017201320092014
Current release3.10.0, March 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedAll OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
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
SQL infoSupport of SQLnowith Databricks SQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheHTTP REST
Supported programming languagesGoPython
R
Scala
JavaGo
Java
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnono
Triggersnoyes infoCache Event Listenersyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoby using Terracotta ServerSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyes infoby using Terracotta Serverselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes infosupports JTA and can work as an XA resourceno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing a tiered cache-storage approachyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnonono
More information provided by the system vendor
BadgerDatabricksEhcacheHawkular Metrics
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
BadgerDatabricksEhcacheHawkular Metrics
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google News

Saudi Arabia’s Sovereign Wealth Fund’s Big AI Bets Include Mistral And Databricks
24 September 2024, Forbes

Databricks could launch IPO in two months but biding time despite investor pressure, CEO says
13 September 2024, ION Analytics

Databricks sues patent holders over alleged 'extortion' scheme
9 September 2024, Reuters

Databricks reportedly paid $2 billion in Tabular acquisition
14 August 2024, TechCrunch

Inside the Snowflake — Databricks Rivalry, and Why Both Fear Microsoft
14 August 2024, Bloomberg

provided by Google News

Jira Data Center user? Here's a critical Ehcache vulnerability to spoil your day
22 July 2021, The Register

Atlassian asks customers to patch critical Jira vulnerability
22 July 2021, BleepingComputer

Critical Jira Flaw in Atlassian Could Lead to RCE
22 July 2021, Threatpost

How to partition Sonatype Nexus Repository: Targets, privileges, and roles
9 February 2010, Sonatype Blog

Implementing fallback with cached data
8 October 2018, O'Reilly Media

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived…
5 June 2019, DevClass

provided by Google News



Share this page

Featured Products

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Present your product here