DBMS > Badger vs. JSqlDb vs. LeanXcale vs. Sadas Engine

System Properties Comparison Badger vs. JSqlDb vs. LeanXcale vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

JavaScript Query Language Database, stores JavaScript objects and primitives

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Key-value store

Document store
Object oriented DBMS

Key-value store
Relational DBMS

Relational DBMS

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

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

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

github.com/dgraph-io/badger

jsqldb.org (offline)

www.leanxcale.com

www.sadasengine.com

Technical documentation

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

DGraph Labs

Konrad von Backstrom

LeanXcale

SADAS s.r.l.

Initial release

2017

2018

2015

2006

Current release

0.8, December 2018

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

free trial version 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.

Implementation language

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

AIX
Linux
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

yes

through Apache Derby

yes

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC
Proprietary protocol

Supported programming languages

JavaScript

C
Java
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

functions in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

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Recent citations in the news

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

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