DBMS > Apache Impala vs. Badger vs. Brytlyt vs. Oracle Coherence

System Properties Comparison Apache Impala vs. Badger vs. Brytlyt vs. Oracle Coherence

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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.

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Oracles in-memory data grid solution

Primary database model

Secondary database models

Document store

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Website

impala.apache.org

github.com/dgraph-io/badger

brytlyt.io

www.oracle.com/java/coherence

Technical documentation

impala.apache.org/impala-docs.html

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

docs.brytlyt.io

docs.oracle.com/en/middleware/standalone/coherence

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DGraph Labs

Brytlyt

Oracle

Initial release

2013

2017

2016

2007

Current release

4.1.0, June 2022

5.0, August 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

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.

Implementation language

C++

C, C++ and CUDA

Java

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

All OS with a Java VM

Data scheme

yes

schema-free

yes

schema-free

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JCache
JPA
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

in PL/pgSQL

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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