DBMS > Adabas vs. Dragonfly vs. Kinetica vs. NCache vs. Snowflake

System Properties Comparison Adabas vs. Dragonfly vs. Kinetica vs. NCache vs. Snowflake

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 drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Fully vectorized database across both GPUs and CPUs

Open-Source and Enterprise in-memory Key-Value Store

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

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Search engine

Using distributed Lucene

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.kinetica.com

www.alachisoft.com/ncache

www.snowflake.com

Technical documentation

www.dragonflydb.io/docs

docs.kinetica.com

www.alachisoft.com/resources/docs

docs.snowflake.net/manuals/index.html

Developer

Software AG

DragonflyDB team and community contributors

Kinetica

Alachisoft

Snowflake Computing Inc.

Initial release

1971

2023

2012

2005

2014

Current release

1.0, March 2023

7.1, August 2021

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

Open Source

Enterprise Edition available

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++

C, C++

C#, .NET, .NET Core, Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux
Windows

hosted

Data scheme

yes

scheme-free

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL-like DML and DDL statements

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

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

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

CLI Client
JDBC
ODBC

Supported programming languages

Natural

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C++
Java
JavaScript (Node.js)
Python

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

Lua

user defined functions

support for stored procedures with SQL-Server CLR

user defined functions

Triggers

publish/subscribe channels provide some trigger functionality

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Notifications

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

yes, with selectable consistency level

yes

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 or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

GPU vRAM or System RAM

yes

User concepts

Access control

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

Password-based authentication

Access rights for users and roles on table level

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

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

More information provided by the system vendor

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