DBMS > Badger vs. EJDB vs. NSDb vs. Oracle Coherence vs. YTsaurus

System Properties Comparison Badger vs. EJDB vs. NSDb vs. Oracle Coherence vs. YTsaurus

Editorial information provided by DB-Engines

Name

Description

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Oracles in-memory data grid solution

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store
Key-value store

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

nsdb.io

www.oracle.com/java/coherence

ytsaurus.tech

Technical documentation

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

github.com/Softmotions/ejdb/blob/master/README.md

nsdb.io/Architecture

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

ytsaurus.tech/docs/en

Developer

DGraph Labs

Softmotions

Oracle

Yandex

Initial release

2017

2012

2017

2007

2023

Current release

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

Open Source

Apache Version 2.0

commercial

Open Source

Apache License, Version 2.0

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, Scala

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

Linux
macOS

All OS with a Java VM

Ubuntu

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

YQL, an SQL-based language, is supported

APIs and other access methods

in-process shared library

gRPC
HTTP REST
WebSocket

JCache
JPA
RESTful HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java
Scala

.Net
C++
Java

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

Access Control Lists

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