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

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

Editorial information provided by DB-Engines

Name

Description

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.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

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

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.gridgain.com

github.com/codenotary/immudb
immudb.io

github.com/Snapchat/KeyDB
keydb.dev

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

www.sap.com/products/hana.html

Technical documentation

www.gridgain.com/docs/index.html

docs.immudb.io

docs.keydb.dev

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

help.sap.com/hana

Developer

GridGain Systems, Inc.

Codenotary

EQ Alpha Technology Ltd.

Microsoft

SAP

Initial release

2007

2020

2019

2010

Current release

GridGain 8.5.1

1.2.3, April 2022

V12

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

BSD-3

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

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux

hosted

Appliance or cloud-service

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

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

SQL-like syntax

yes

APIs and other access methods

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

gRPC protocol
PostgreSQL wire protocol

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

Server-side scripts

Stored procedures

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

Lua

Transact SQL

SQLScript, R

Triggers

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

yes (replicated cache)

Multi-source replication
Source-replica replication

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

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Security Hooks for custom implementations

simple password-based access control and ACL

fine grained access rights according to SQL-standard

yes

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