DBMS > atoti vs. EsgynDB vs. FatDB vs. Hypertable vs. ScyllaDB

System Properties Comparison atoti vs. EsgynDB vs. FatDB vs. Hypertable vs. ScyllaDB

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.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Cassandra and DynamoDB compatible wide column store

Primary database model

Object oriented DBMS

Relational DBMS

Document store
Key-value store

Wide column store

Secondary database models

Key-value store

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

atoti.io

www.esgyn.cn

www.scylladb.com

Technical documentation

docs.atoti.io

docs.scylladb.com

Developer

ActiveViam

Esgyn

FatCloud

Hypertable Inc.

ScyllaDB

Initial release

2015

2012

2009

2015

Current release

0.9.8.11, March 2016

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

GNU version 3. Commercial license available

Open Source

Open Source (AGPL), commercial license available

Cloud-based only

Only available as a cloud service

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

Java

C++, Java

C++

Server operating systems

Linux

Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

yes

schema-free

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

cluster global secondary indices

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

Via inetgration in SQL Server

SQL-like DML and DDL statements (CQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

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

C++ API
Thrift

Proprietary protocol (CQL)

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

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++
Java
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

Python

Java Stored Procedures

yes

via applications

yes, Lua

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

selectable replication factor on file system level

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

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...
» more

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
» more

Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
» more

Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more

Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more

Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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