DBMS > Google Cloud Bigtable vs. Lovefield vs. Trino vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. Lovefield vs. Trino vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Wide column store

Relational DBMS

Document store

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	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

cloud.google.com/bigtable

google.github.io/lovefield

trino.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cloud.google.com/bigtable/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

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

www.xtdb.com/docs

Developer

Google

Trino Software Foundation

Juxt Ltd.

Initial release

2015

2014

2012

2020 rebranded from PrestoSQL

2019

Current release

2.1.12, February 2017

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java

Clojure

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS

for devlopment

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

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

JDBC
RESTful HTTP API
Trino CLI

HTTP REST
JDBC

Supported programming languages

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

JavaScript

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Clojure
Java

Server-side scripts

Stored procedures

yes, depending on connected data-source

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

depending on connected data-source

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

depending on connected data-source

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

depending on connected data-source

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

depending on connected data-source

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

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

SQL standard access control

More information provided by the system vendor

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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More resources

Recent citations in the news

Google Cloud adds graph processing to Spanner, SQL support to Bigtable
1 August 2024, InfoWorld

Google introduces Bigtable SQL access and Spanner's new AI-ready features
1 August 2024, ZDNet

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1 March 2024, Forbes

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1 August 2024, The New Stack

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29 February 2024, VentureBeat

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30 April 2024, The Next Platform

A look at Presto, Trino SQL query engines
9 August 2022, TechTarget

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30 March 2022, hackernoon.com

Query big data with resilience using Trino in Amazon EMR with Amazon EC2 Spot Instances for less cost
4 October 2023, AWS Blog

Starburst accelerates Trino to ‘Warp Speed’ to accelerate data querying
8 February 2023, VentureBeat

provided by Google News

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