DBMS > Apache Impala vs. Badger vs. Dolt vs. Ignite vs. MySQL

System Properties Comparison Apache Impala vs. Badger vs. Dolt vs. Ignite vs. MySQL

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A MySQL compatible DBMS with Git-like versioning of data and schema

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Widely used open source RDBMS

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

impala.apache.org

github.com/dgraph-io/badger

github.com/dolthub/dolt
www.dolthub.com

ignite.apache.org

www.mysql.com

Technical documentation

impala.apache.org/impala-docs.html

godoc.org/github.com/dgraph-io/badger

docs.dolthub.com

apacheignite.readme.io/docs

dev.mysql.com/doc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DGraph Labs

DoltHub Inc

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2013

2017

2018

2015

1995

Current release

4.1.0, June 2022

Apache Ignite 2.6

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C++

C++, Java, .Net

C and C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
C++
Java
PHP
Python
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

currently in alpha release

yes (compute grid and cache interceptors can be used instead)

yes

proprietary syntax

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes (replicated cache)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Only one user is configurable, and must be specified in the config file at startup

Security Hooks for custom implementations

Users with fine-grained authorization concept

no user groups or roles

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