DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Badger vs. HBase vs. Spark SQL

System Properties Comparison Badger vs. HBase vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Wide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#325  Overall
#49  Key-value stores
Score31.25
Rank#26  Overall
#2  Wide column stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerhbase.apache.orgspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release201720082014
Current release2.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROyes
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.nonono
Secondary indexesnonono
SQL infoSupport of SQLnonoSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Supported programming languagesGoC
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)no
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.noyesno
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

More information provided by the system vendor

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
BadgerHBaseSpark SQL
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

HBase: The database big data left behind
6 May 2016, InfoWorld

What Is HBase? (Definition, Uses, Benefits, Features)
22 December 2022, Built In

HBase Tutorial
24 February 2023, Simplilearn

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News



Share this page

Featured Products

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

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

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it 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

Present your product here