DBMS > Databend vs. Graph Engine vs. Immudb vs. SAP HANA

System Properties Comparison Databend vs. Graph Engine vs. Immudb vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

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

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Key-value store

Relational DBMS

Secondary database models

Relational 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	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

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

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.graphengine.io

github.com/codenotary/immudb
immudb.io

www.sap.com/products/hana.html

Technical documentation

docs.databend.com

www.graphengine.io/docs/manual

docs.immudb.io

help.sap.com/hana

Developer

Databend Labs

Microsoft

Codenotary

SAP

Initial release

2021

2010

2020

2010

Current release

1.0.59, April 2023

1.2.3, April 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

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

Rust

.NET and C

Server operating systems

hosted
Linux
macOS

.NET

BSD
Linux
macOS
Solaris
Windows
z/OS

Appliance or cloud-service

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like syntax

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP API

gRPC protocol
PostgreSQL wire protocol

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

C#
C++
F#
Visual Basic

.Net
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

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

User concepts

Access control

Users with fine-grained authorization concept, user roles

yes

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