DBMS > Adabas vs. Graph Engine vs. Microsoft SQL Server vs. ScyllaDB vs. Vertica

System Properties Comparison Adabas vs. Graph Engine vs. Microsoft SQL Server vs. ScyllaDB vs. Vertica

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Microsofts flagship relational DBMS

Cassandra and DynamoDB compatible wide column store

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Multivalue DBMS

Graph DBMS
Key-value store

Relational DBMS

Wide column store

Relational DBMS

Column oriented

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Key-value store

Spatial DBMS
Time Series DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

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

www.graphengine.io

www.microsoft.com/en-us/sql-server

www.scylladb.com

www.vertica.com

Technical documentation

www.graphengine.io/docs/manual

learn.microsoft.com/en-US/sql/sql-server

docs.scylladb.com

vertica.com/documentation

Developer

Software AG

Microsoft

ScyllaDB

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1971

2010

1989

2015

2005

Current release

SQL Server 2022, November 2022

ScyllaDB Open Source 5.4.1, January 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

restricted free version is available

Open Source

Open Source (AGPL), commercial license available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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

.NET and C

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

.NET

Linux
Windows

Linux

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like DML and DDL statements (CQL)

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Proprietary protocol (CQL)

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

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Natural

C#
C++
F#
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

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

Server-side scripts

Stored procedures

in Natural

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes, Lua

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes, but depending on the SQL-Server Edition

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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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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Cost-based models and subscription-based models are both available. One license is...
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