DBMS > EXASOL vs. Google Cloud Firestore vs. ScyllaDB vs. Snowflake vs. WakandaDB

System Properties Comparison EXASOL vs. Google Cloud Firestore vs. ScyllaDB vs. Snowflake vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Cassandra and DynamoDB compatible wide column store

Cloud-based data warehousing service for structured and semi-structured data

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Key-value store

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

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	5.27
Rank	#67	Overall
	#5	Wide column stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Website

www.exasol.com

firebase.google.com/products/firestore

www.scylladb.com

www.snowflake.com

wakanda.github.io

Technical documentation

www.exasol.com/resources

firebase.google.com/docs/firestore

docs.scylladb.com

docs.snowflake.net/manuals/index.html

wakanda.github.io/doc

Developer

Exasol

Google

ScyllaDB

Snowflake Computing Inc.

Wakanda SAS

Initial release

2000

2017

2015

2014

2012

Current release

ScyllaDB Open Source 5.4.1, January 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Open Source (AGPL), commercial license available

commercial

Open Source

AGPLv3, extended commercial license available

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.

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Implementation language

C++

C++, JavaScript

Server operating systems

hosted

Linux

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL)

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

Java
Lua
Python
R

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

yes, Lua

user defined functions

yes

Triggers

yes

yes, with Cloud Functions

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

Representation of geographical distribution of servers is possible

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Atomicity and isolation are supported for single operations

ACID

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

in-memory tables

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users can be defined per object

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

yes

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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