DBMS > Apache Drill vs. Badger vs. etcd vs. Transbase

System Properties Comparison Apache Drill vs. Badger vs. etcd vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

A distributed reliable key-value store

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

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

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

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

drill.apache.org

github.com/dgraph-io/badger

etcd.io
github.com/etcd-io/etcd

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

Technical documentation

drill.apache.org/docs

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

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

Developer

Apache Software Foundation

DGraph Labs

Transaction Software GmbH

Initial release

2012

2017

1987

Current release

1.20.3, January 2023

3.4, August 2019

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
Windows

experimental

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
JSON over HTTP

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

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

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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More resources

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28 March 2022, iProgrammer

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