DBMS > etcd vs. Machbase Neo vs. Sphinx vs. Yaacomo

System Properties Comparison etcd vs. Machbase Neo vs. Sphinx vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A distributed reliable key-value store

TimeSeries DBMS for AIoT and BigData

Open source search engine for searching in data from different sources, e.g. relational databases

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

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

machbase.com

sphinxsearch.com

yaacomo.com

Technical documentation

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

machbase.com/dbms

sphinxsearch.com/docs

Developer

Machbase

Sphinx Technologies Inc.

Q2WEB GmbH

Initial release

2013

2001

2009

Current release

3.4, August 2019

V8.0, August 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

Open Source

GPL version 2, commercial licence available

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Android
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

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (SphinxQL)

yes

APIs and other access methods

gRPC
JSON over HTTP

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

Proprietary protocol

JDBC
ODBC

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++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

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

none

Source-replica replication

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

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

The original contents of fields are not stored in the Sphinx index.

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

More information provided by the system vendor

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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