DBMS > Elasticsearch vs. FoundationDB vs. Graph Engine vs. Snowflake vs. Sphinx

System Properties Comparison Elasticsearch vs. FoundationDB vs. Graph Engine vs. Snowflake vs. Sphinx

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Ordered key-value store. Core features are complimented by layers.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

Search engine

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Graph DBMS
Key-value store

Relational DBMS

Search engine

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.elastic.co/elasticsearch

github.com/apple/foundationdb

www.graphengine.io

www.snowflake.com

sphinxsearch.com

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

apple.github.io/foundationdb

www.graphengine.io/docs/manual

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Developer

Elastic

FoundationDB

Microsoft

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

2010

2013

2010

2014

2001

Current release

8.6, January 2023

6.2.28, November 2020

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

Open Source

MIT License

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

.NET and C

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

.NET

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

some layers support schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

some layers support typing

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

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

supported in specific SQL layer only

yes

SQL-like query language (SphinxQL)

APIs and other access methods

Java API
RESTful HTTP/JSON API

RESTful HTTP API

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C#
C++
F#
Visual Basic

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

in SQL-layer only

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Memcached and Redis integration

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.