DBMS > Apache Kylin vs. Google Cloud Datastore vs. Snowflake vs. Trino vs. XTDB

System Properties Comparison Apache Kylin vs. Google Cloud Datastore vs. Snowflake vs. Trino vs. XTDB

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

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

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

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	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

kylin.apache.org

cloud.google.com/datastore

www.snowflake.com

trino.io

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

Technical documentation

kylin.apache.org/docs

cloud.google.com/datastore/docs

docs.snowflake.net/manuals/index.html

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

www.xtdb.com/docs

Social network pages

Developer

Apache Software Foundation, originally contributed from eBay Inc

Google

Snowflake Computing Inc.

Trino Software Foundation

Juxt Ltd.

Initial release

2015

2008

2014

2012

2020 rebranded from PrestoSQL

2019

Current release

3.1.0, July 2020

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

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

Java

Clojure

Server operating systems

Linux

hosted

Linux
macOS

for devlopment

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

Data scheme

yes

schema-free

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

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.

yes

Secondary indexes

yes

depending on connected data-source

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SQL-like query language (GQL)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

HTTP REST
JDBC

Supported programming languages

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

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Clojure
Java

Server-side scripts

Stored procedures

using Google App Engine

user defined functions

yes, depending on connected data-source

Triggers

Callbacks using the Google Apps Engine

similar concept for controling cloud resources

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

Multi-source replication using Paxos

yes

depending on connected data-source

yes, each node contains all data

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

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

depending on connected data-source

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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, 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.

User concepts

Access control

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

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

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

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Market metrics

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

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