DBMS > Adabas vs. HEAVY.AI vs. Immudb vs. Snowflake

System Properties Comparison Adabas vs. HEAVY.AI vs. Immudb vs. Snowflake

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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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

github.com/heavyai/heavydb
www.heavy.ai

github.com/codenotary/immudb
immudb.io

www.snowflake.com

Technical documentation

docs.heavy.ai

docs.immudb.io

docs.snowflake.net/manuals/index.html

Developer

Software AG

HEAVY.AI, Inc.

Codenotary

Snowflake Computing Inc.

Initial release

1971

2016

2020

2014

Current release

5.10, January 2022

1.2.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0

commercial

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.

Implementation language

C++ and CUDA

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

BSD
Linux
macOS
Solaris
Windows
z/OS

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like syntax

yes

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

JDBC
ODBC
Thrift
Vega

gRPC protocol
PostgreSQL wire protocol

CLI Client
JDBC
ODBC

Supported programming languages

Natural

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Round robin

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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