DBMS > chDB vs. EventStoreDB vs. Google Cloud Bigtable vs. SwayDB

System Properties Comparison chDB vs. EventStoreDB vs. Google Cloud Bigtable vs. SwayDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embedded SQL OLAP Engine powered by ClickHouse

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Event Store

Key-value store
Wide column store

Key-value store

Secondary database models

Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

github.com/chdb-io/chdb

www.eventstore.com

cloud.google.com/bigtable

swaydb.simer.au

Technical documentation

doc.chdb.io

developers.eventstore.com

cloud.google.com/bigtable/docs

Developer

Event Store Limited

Google

Simer Plaha

Initial release

2023

2012

2015

2018

Current release

21.2, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Open Source

GNU Affero GPL V3.0

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.

Implementation language

Scala

Server operating systems

server-less

Linux
Windows

hosted

Data scheme

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

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

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

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)

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

More information provided by the system vendor

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

Share this page