DBMS > Dragonfly vs. GridGain vs. Immudb vs. Microsoft Azure SQL Database vs. SAP HANA

System Properties Comparison Dragonfly vs. GridGain vs. Immudb vs. Microsoft Azure SQL Database vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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

GridGain is an in-memory computing platform, built on Apache Ignite

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

Database as a Service offering with high compatibility to Microsoft SQL Server

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key-value store

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

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

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

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

www.gridgain.com

github.com/codenotary/immudb
immudb.io

azure.microsoft.com/en-us/products/azure-sql/database

www.sap.com/products/hana.html

Technical documentation

www.dragonflydb.io/docs

www.gridgain.com/docs/index.html

docs.immudb.io

docs.microsoft.com/en-us/azure/azure-sql

help.sap.com/hana

Developer

DragonflyDB team and community contributors

GridGain Systems, Inc.

Codenotary

Microsoft

SAP

Initial release

2023

2007

2020

2010

Current release

1.0, March 2023

GridGain 8.5.1

1.2.3, April 2022

V12

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java, C++, .Net

C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

BSD
Linux
macOS
Solaris
Windows
z/OS

hosted

Appliance or cloud-service

Data scheme

scheme-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

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

ANSI-99 for query and DML statements, subset of DDL

SQL-like syntax

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

gRPC protocol
PostgreSQL wire protocol

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

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#
C++
Java
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes (compute grid and cache interceptors can be used instead)

Transact SQL

SQLScript, R

Triggers

publish/subscribe channels provide some trigger functionality

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Password-based authentication

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

yes

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