DBMS > FatDB vs. Google BigQuery vs. GridDB vs. ScyllaDB

System Properties Comparison FatDB vs. Google BigQuery vs. GridDB vs. ScyllaDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Large scale data warehouse service with append-only tables

Scalable in-memory time series database optimized for IoT and Big Data

Cassandra and DynamoDB compatible wide column store

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Wide column store

Secondary database models

Key-value store
Relational DBMS

Key-value store

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

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	4.15
Rank	#69	Overall
	#5	Wide column stores

Website

cloud.google.com/bigquery

griddb.net

www.scylladb.com

Technical documentation

cloud.google.com/bigquery/docs

docs.griddb.net

docs.scylladb.com

Developer

FatCloud

Google

Toshiba Corporation

ScyllaDB

Initial release

2012

2010

2013

2015

Current release

5.1, August 2022

ScyllaDB Open Source 6.0.2, July 2024

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Open Source (AGPL), 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.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

C++

Server operating systems

Windows

hosted

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

cluster global secondary indices

SQL

Support of SQL

Via inetgration in SQL Server

yes

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like DML and DDL statements (CQL)

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Proprietary protocol (CQL)

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

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

Server-side scripts

Stored procedures

yes

via applications

user defined functions

in JavaScript

yes, Lua

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

ACID at container level

Atomicity and isolation are supported for single 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

in-memory tables

User concepts

Access control

Can implement custom security layer via applications

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per database

Access rights for users can be defined per object

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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