DBMS > GeoSpock vs. IRONdb vs. Snowflake vs. Sphinx

System Properties Comparison GeoSpock vs. IRONdb vs. Snowflake vs. Sphinx

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Spatial and temporal data processing engine for extreme data scale

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

Secondary database models

Time Series DBMS

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

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

geospock.com

www.circonus.com/solutions/time-series-database/

www.snowflake.com

sphinxsearch.com

Technical documentation

docs.circonus.com/irondb/category/getting-started

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Developer

GeoSpock

Circonus LLC.

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

2017

2014

2001

Current release

2.0, September 2019

V0.10.20, January 2018

3.5.1, February 2023

License

Commercial or Open Source

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, Javascript

C and C++

C++

Server operating systems

hosted

Linux

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

temporal, categorical

yes

full-text index on all search fields

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC

HTTP API

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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 Lua

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Automatic, metric affinity per node

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

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.

User concepts

Access control

Access rights for users can be defined per table

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.