DBMS > Dgraph vs. Google Cloud Bigtable vs. Tarantool vs. Trino vs. Yanza

System Properties Comparison Dgraph vs. Google Cloud Bigtable vs. Tarantool vs. Trino vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

Distributed and scalable native Graph DBMS

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

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

Time Series DBMS for IoT Applications

Primary database model

Graph DBMS

Key-value store
Wide column store

Document store
Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

dgraph.io

cloud.google.com/bigtable

www.tarantool.io

trino.io

yanza.com

Technical documentation

dgraph.io/docs

cloud.google.com/bigtable/docs

www.tarantool.io/en/doc

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

Social network pages

Developer

Dgraph Labs, Inc.

Google

Trino Software Foundation

Yanza

Initial release

2016

2015

2008

2012

2020 rebranded from PrestoSQL

2015

Current release

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Open Source

Apache Version 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

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 and C++

Java

Server operating systems

Linux
OS X
Windows

hosted

BSD
Linux
macOS

Linux
macOS

for devlopment

Windows

Data scheme

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

yes

schema-free

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

Full-featured ANSI SQL support

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Open binary protocol

JDBC
RESTful HTTP API
Trino CLI

HTTP API

Supported programming languages

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

C#
C++
Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Go
Java
JavaScript (Node.js)
Python
R
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

Lua, C and SQL stored procedures

yes, depending on connected data-source

Triggers

yes, before/after data modification events, on replication events, client session events

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

depending on connected data-source

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Internal replication in Colossus, and regional replication between two clusters in different zones

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

depending on connected data-source

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

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

Atomic single-row operations

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

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, full featured in-memory storage engine with persistence

User concepts

Access control

Planned for future releases

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

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
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

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22 May 2024

Big names round out the Trino Fest 2024 lineup
8 May 2024

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

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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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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