DBMS > Apache Druid vs. Lovefield vs. Sphinx vs. Yaacomo

System Properties Comparison Apache Druid vs. Lovefield 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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Embeddable relational database for web apps written in pure JavaScript

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

Relational DBMS
Time Series DBMS

Relational DBMS

Search engine

Relational DBMS

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

druid.apache.org

google.github.io/lovefield

sphinxsearch.com

yaacomo.com

Technical documentation

druid.apache.org/docs/latest/design

github.com/google/lovefield/blob/master/docs/spec_index.md

sphinxsearch.com/docs

Developer

Apache Software Foundation and contributors

Google

Sphinx Technologies Inc.

Q2WEB GmbH

Initial release

2012

2014

2001

2009

Current release

29.0.1, April 2024

2.1.12, February 2017

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

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

Java

JavaScript

C++

Server operating systems

Linux
OS X
Unix

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Android
Linux
Windows

Data scheme

yes

schema-less columns are supported

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 for querying

SQL-like query language

via JavaScript builder pattern

SQL-like query language (SphinxQL)

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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More resources

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