DBMS > etcd vs. Machbase Neo vs. RocksDB vs. Teradata Aster

System Properties Comparison etcd vs. Machbase Neo vs. RocksDB vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

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)

Platform for big data analytics on multistructured data sources and types

Primary database model

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	3.41
Rank	#86	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.

Teradata

Initial release

2013

2005

Current release

3.4, August 2019

V8.0, August 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

Open Source

BSD

commercial

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

FreeBSD
Linux
Windows

experimental

Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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.

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
JSON over HTTP

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

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB

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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

R packages

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

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

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

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

fine grained access rights according to SQL-standard

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