DBMS > GeoSpock vs. Informix vs. Kinetica vs. Snowflake vs. TerarkDB

System Properties Comparison GeoSpock vs. Informix vs. Kinetica vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

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

Description

Spatial and temporal data processing engine for extreme data scale

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

Fully vectorized database across both GPUs and CPUs

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

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

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Spatial DBMS
Time Series DBMS

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

Score	17.87
Rank	#35	Overall
	#22	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

geospock.com

www.ibm.com/products/informix

www.kinetica.com

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

docs.kinetica.com

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

GeoSpock

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Kinetica

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

1984

2012

2014

2016

Current release

2.0, September 2019

14.10.FC5, November 2020

7.1, August 2021

License

Commercial or Open Source

commercial

free developer edition 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

Java, Javascript

C, C++ and Java

C, C++

C++

Server operating systems

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

hosted

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

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 or Eventual Consistency depending on configuration

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

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users can be defined per table

Users with fine-grained authentication, authorization, and auditing controls

Access rights for users and roles on table level

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.