DBMS > Apache Druid vs. Badger vs. Brytlyt vs. Transbase

System Properties Comparison Apache Druid vs. Badger vs. Brytlyt vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

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

Score	2.70
Rank	#98	Overall
	#50	Relational DBMS
	#7	Time Series DBMS

Score	0.18
Rank	#314	Overall
	#45	Key-value stores

Score	0.25
Rank	#294	Overall
	#133	Relational DBMS

Score	0.04
Rank	#359	Overall
	#152	Relational DBMS

Website

druid.apache.org

github.com/dgraph-io/badger

brytlyt.io

www.transaction.de/en/products/transbase.html

Technical documentation

druid.apache.org/docs/latest/design

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

docs.brytlyt.io

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation and contributors

DGraph Labs

Brytlyt

Transaction Software GmbH

Initial release

2012

2017

2016

1987

Current release

30.0.0, June 2024

5.0, August 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

commercial

free development license

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

Java

C, C++ and CUDA

C and C++

Server operating systems

Linux
OS X
Unix

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-less columns are supported

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

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

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

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.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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