DBMS > PostGIS vs. Snowflake vs. Sphinx vs. TerarkDB

System Properties Comparison PostGIS vs. Snowflake vs. Sphinx vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of PostgreSQL

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Relational DBMS

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

Score	20.16
Rank	#29	Overall
	#1	Spatial DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

postgis.net

www.snowflake.com

sphinxsearch.com

github.com/bytedance/terarkdb

Technical documentation

postgis.net/documentation

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Snowflake Computing Inc.

Sphinx Technologies Inc.

ByteDance, originally Terark

Initial release

2005

2014

2001

2016

Current release

3.4.2, February 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

GPL v2.0

commercial

Open Source

GPL version 2, commercial licence available

commercial

restricted open source version 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

C++

Server operating systems

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

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

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

CLI Client
JDBC
ODBC

Proprietary protocol

C++ API
Java API

Supported programming languages

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

based on PostgreSQL

yes

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on PostgreSQL

yes

none

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

User concepts

Access control

yes

based on PostgreSQL

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

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