DBMS > GridDB vs. Snowflake vs. Trino vs. WakandaDB

System Properties Comparison GridDB vs. Snowflake vs. Trino vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

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

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Time Series DBMS

Relational DBMS

Object oriented DBMS

Secondary database models

Key-value store
Relational DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

docs.griddb.net

docs.snowflake.net/manuals/index.html

trino.io/broadcast
trino.io/docs/current

wakanda.github.io/doc

Social network pages

Developer

Toshiba Corporation

Snowflake Computing Inc.

Trino Software Foundation

Wakanda SAS

Initial release

2013

2014

2012

2020 rebranded from PrestoSQL

2012

Current release

5.1, August 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Open Source

Apache Version 2.0

Open Source

AGPLv3, extended commercial license 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.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

C++

Java

C++, JavaScript

Server operating systems

Linux

hosted

Linux
macOS

for devlopment

Linux
OS X
Windows

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

depending on connected data-source

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

RESTful HTTP API

Supported programming languages

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

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes, depending on connected data-source

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on connected data-source

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

depending on connected data-source

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

depending on connected data-source

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID at container level

ACID

depending on connected data-source

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

depending on connected data-source

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 can be defined per database

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

SQL standard access control

yes

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
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Trino is the fastest open source, massively parallel processing SQL query engine...
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Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Trino is widely adopted across the globe as freely-available open source software....
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Market metrics

GitHub trending repository
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33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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Trino is an open source project and usage is therefore free. Commercial offerings...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.