DBMS > etcd vs. Machbase Neo vs. RocksDB

System Properties Comparison etcd vs. Machbase Neo vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Key-value store

Time Series DBMS

Key-value store

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

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Score	0.22
Rank	#324	Overall
	#29	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

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

machbase.com

rocksdb.org

Technical documentation

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

machbase.com/dbms

github.com/facebook/rocksdb/wiki

Developer

Machbase

Facebook, Inc.

Initial release

2013

Current release

3.4, August 2019

V8.0, August 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

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

Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-free

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-like query language

APIs and other access methods

gRPC
JSON over HTTP

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

yes

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

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

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

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