DBMS > Adabas vs. atoti vs. Lovefield vs. Realm vs. ScyllaDB

System Properties Comparison Adabas vs. atoti vs. Lovefield vs. Realm vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

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

Embeddable relational database for web apps written in pure JavaScript

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Cassandra and DynamoDB compatible wide column store

Primary database model

Secondary database models

Key-value store

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

atoti.io

google.github.io/lovefield

realm.io

www.scylladb.com

Technical documentation

docs.atoti.io

github.com/google/lovefield/blob/master/docs/spec_index.md

realm.io/docs

docs.scylladb.com

Developer

Software AG

ActiveViam

Google

Realm, acquired by MongoDB in May 2019

ScyllaDB

Initial release

1971

2014

2015

Current release

2.1.12, February 2017

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

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

JavaScript

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Android
Backend: server-less
iOS
Windows

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

cluster global secondary indices

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

Multidimensional Expressions (MDX)

SQL-like query language

via JavaScript builder pattern

SQL-like DML and DDL statements (CQL)

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

Proprietary protocol (CQL)

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

Supported programming languages

Natural

JavaScript

.Net
Java

with Android only
Objective-C
React Native
Swift

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

in Natural

Python

runs within the applications so server-side scripts are unnecessary

yes, Lua

Triggers

Using read-only observers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

In-Memory realm

yes

in-memory tables

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

yes

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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