DBMS > Google Cloud Datastore vs. LevelDB vs. ToroDB vs. Trino

System Properties Comparison Google Cloud Datastore vs. LevelDB vs. ToroDB vs. Trino

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Editorial information provided by DB-Engines

Name

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

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A MongoDB-compatible JSON document store, built on top of PostgreSQL

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

Primary database model

Secondary database models

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	4.47
Rank	#76	Overall
	#12	Document stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

cloud.google.com/datastore

github.com/google/leveldb

github.com/torodb/server

trino.io

Technical documentation

cloud.google.com/datastore/docs

github.com/google/leveldb/blob/main/doc/index.md

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

Social network pages

Developer

Google

8Kdata

Trino Software Foundation

Initial release

2008

2011

2016

2012

2020 rebranded from PrestoSQL

Current release

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

AGPL-V3

Open Source

Apache Version 2.0

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

Server operating systems

hosted

Illumos
Linux
OS X
Windows

All OS with a Java 7 VM

Linux
macOS

for devlopment

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

SQL-like query language (GQL)

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

using Google App Engine

yes, depending on connected data-source

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

depending on connected data-source

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, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

SQL standard access control

More information provided by the system vendor

Specific characteristics

Trino is the fastest open source, massively parallel processing SQL query engine...
» more

Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
» more

Typical application scenarios

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

Key customers

Trino is widely adopted across the globe as freely-available open source software....
» more

Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more

Licensing and pricing models

Trino is an open source project and usage is therefore free. Commercial offerings...
» more

News

59: Querying Trino with Java and jOOQ
24 April 2024

A sneak peek of Trino Fest 2024
15 April 2024

Time travel in Delta Lake connector
11 April 2024

58: Understanding your users with Trino and Mitzu
4 April 2024

57: Seeing clearly with OpenTelemetry
14 March 2024

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.

Related products and services

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