DBMS > Databend vs. GBase vs. HBase vs. Ignite vs. SAP HANA

System Properties Comparison Databend vs. GBase vs. HBase vs. Ignite vs. SAP HANA

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

Primary database model

Relational DBMS

Wide column store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

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	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

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

www.gbase.cn

hbase.apache.org

ignite.apache.org

www.sap.com/products/hana.html

Technical documentation

docs.databend.com

hbase.apache.org/book.html

apacheignite.readme.io/docs

help.sap.com/hana

Developer

Databend Labs

General Data Technology Co., Ltd.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Apache Software Foundation

SAP

Initial release

2021

2004

2008

2015

2010

Current release

1.0.59, April 2023

GBase 8a, GBase 8s, GBase 8c

2.3.4, January 2021

Apache Ignite 2.6

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache version 2

Open Source

Apache 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

C, Java, Python

Java

C++, Java, .Net

Server operating systems

hosted
Linux
macOS

Linux

Linux
Unix
Windows

using Cygwin

Linux
OS X
Solaris
Windows

Appliance or cloud-service

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

Standard with numerous extensions

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

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
Thrift

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

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Coprocessors in Java

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

SQLScript, R

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Single row ACID (across millions of columns)

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

Users with fine-grained authorization concept, user roles

yes

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Security Hooks for custom implementations

yes

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