DBMS > etcd vs. jBASE vs. RocksDB

System Properties Comparison etcd vs. jBASE vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

A robust multi-value DBMS comprising development tools and middleware

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store

Multivalue DBMS

Key-value store

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

Score	8.60
Rank	#53	Overall
	#6	Key-value stores

Score	2.07
Rank	#140	Overall
	#3	Multivalue DBMS

Score	4.57
Rank	#87	Overall
	#13	Key-value stores

Website

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

www.jbase.com

rocksdb.org

Technical documentation

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

docs.zumasys.com/jbase

github.com/facebook/rocksdb/wiki

Developer

Zumasys

Facebook, Inc.

Initial release

1991

2013

Current release

3.4, August 2019

5.7

7.10.2, March 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
Linux
Windows

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

optional

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

Secondary indexes

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

APIs and other access methods

gRPC
JSON over HTTP

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

C++ API
Java API

Supported programming languages

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

.Net
Basic
Jabbascript
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

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

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

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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.

yes

User concepts

Access control

Access rights can be defined down to the item level

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