DBMS > Databend vs. Galaxybase vs. Netezza vs. SiriDB vs. SpaceTime

System Properties Comparison Databend vs. Galaxybase vs. Netezza vs. SiriDB vs. SpaceTime

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

Scalable, ACID-compliant native distributed parallel graph platform

Data warehouse and analytics appliance part of IBM PureSystems

Open Source Time Series DBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Secondary database models

Relational DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

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

galaxybase.com

www.ibm.com/products/netezza

siridb.com

www.mireo.com/spacetime

Technical documentation

docs.databend.com

docs.siridb.com

Developer

Databend Labs

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

IBM

Cesbit

Mireo

Initial release

2021

2017

2000

2017

2020

Current release

1.0.59, April 2023

Nov 20, November 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

commercial

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

Rust

C and Java

C++

Server operating systems

hosted
Linux
macOS

Linux

included in appliance

Linux

Data scheme

yes

Strong typed schema

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

A subset of ANSI SQL is implemented

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

JDBC
ODBC
OLE DB

HTTP API

RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Go
Java
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C#
C++
Python

Server-side scripts

Stored procedures

user defined procedures and functions

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

Real-time block device replication (DRBD)

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

Relationships in graphs

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

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

Role-based access control

Users with fine-grained authorization concept

simple rights management via user accounts

yes

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