DBMS > Altibase vs. GeoMesa vs. Snowflake vs. Sphinx

System Properties Comparison Altibase vs. GeoMesa vs. Snowflake vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

www.geomesa.org/documentation/stable/user/index.html

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Developer

Altibase

CCRi and others

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

1999

2014

2001

Current release

v7.3, 2023, August 2023

5.0.0, May 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache License 2.0

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

C++

Scala

C++

Server operating systems

AIX
HP-UX
Linux

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

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

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

ANSI SQL-92

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC
Proprietary protocol

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

C
C++
Java

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

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.

In-memory capabilities

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

yes

depending on storage layer

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

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

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