DBMS > atoti vs. FatDB vs. Newts vs. ScyllaDB vs. XTDB

System Properties Comparison atoti vs. FatDB vs. Newts vs. ScyllaDB vs. XTDB

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

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

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

Time Series DBMS based on Cassandra

Cassandra and DynamoDB compatible wide column store

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

Primary database model

Object oriented DBMS

Document store
Key-value store

Time Series DBMS

Wide column store

Document 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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

atoti.io

opennms.github.io/newts

www.scylladb.com

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

Technical documentation

docs.atoti.io

github.com/OpenNMS/newts/wiki

docs.scylladb.com

www.xtdb.com/docs

Developer

ActiveViam

FatCloud

OpenNMS Group

ScyllaDB

Juxt Ltd.

Initial release

2012

2014

2015

2019

Current release

ScyllaDB Open Source 5.4.1, January 2024

1.19, September 2021

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache 2.0

Open Source

Open Source (AGPL), commercial license available

Open Source

MIT License

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++

Clojure

Server operating systems

Windows

Linux
OS X
Windows

Linux

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

Data scheme

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

cluster global secondary indices

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

Via inetgration in SQL Server

SQL-like DML and DDL statements (CQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

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

HTTP REST
Java API

Proprietary protocol (CQL)

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

HTTP REST
JDBC

Supported programming languages

Java

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

Clojure
Java

Server-side scripts

Stored procedures

Python

yes

via applications

yes, Lua

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

Representation of geographical distribution of servers is possible

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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.

yes

in-memory tables

User concepts

Access control

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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