DBMS > EXASOL vs. GeoSpock vs. Netezza vs. Snowflake vs. TigerGraph

System Properties Comparison EXASOL vs. GeoSpock vs. Netezza vs. Snowflake vs. TigerGraph

Editorial information provided by DB-Engines

Name

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

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Spatial and temporal data processing engine for extreme data scale

Data warehouse and analytics appliance part of IBM PureSystems

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.exasol.com

geospock.com

www.ibm.com/products/netezza

www.snowflake.com

www.tigergraph.com

Technical documentation

www.exasol.com/resources

docs.snowflake.net/manuals/index.html

docs.tigergraph.com

Developer

Exasol

GeoSpock

IBM

Snowflake Computing Inc.

Initial release

2000

2014

2017

Current release

2.0, September 2019

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Javascript

C++

Server operating systems

hosted

Linux

included in appliance

hosted

Linux

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

temporal, categorical

yes

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

yes

SQL-like query language (GSQL)

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Java
Lua
Python
R

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Access rights for users can be defined per table

Users with fine-grained authorization concept

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

Role-based access control

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