DBMS > Axibase vs. Databend vs. Graph Engine vs. HyperSQL

System Properties Comparison Axibase vs. Databend vs. Graph Engine vs. HyperSQL

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

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

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Website

axibase.com/docs/atsd/finance

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

www.graphengine.io

hsqldb.org

Technical documentation

docs.databend.com

www.graphengine.io/docs/manual

hsqldb.org/web/hsqlDocsFrame.html

Developer

Axibase Corporation

Databend Labs

Microsoft

Initial release

2013

2021

2010

2001

Current release

15585

1.0.59, April 2023

2.7.2, June 2023

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

based on BSD license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Rust

.NET and C

Java

Server operating systems

Linux

hosted
Linux
macOS

.NET

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Go
Java
JavaScript (Node.js)
Python
Rust

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

yes

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

fine grained access rights according to SQL-standard

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