DBMS > Citus vs. Databend vs. NSDb vs. TimesTen

System Properties Comparison Citus vs. Databend vs. NSDb vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.citusdata.com

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

nsdb.io

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.citusdata.com

docs.databend.com

nsdb.io/Architecture

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Databend Labs

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2010

2021

2017

1998

Current release

8.1, December 2018

1.0.59, April 2023

Release 22.1

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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

Java, Scala

Server operating systems

Linux

hosted
Linux
macOS

Linux
macOS

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, 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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)
Python
Rust

Java
Scala

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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More resources

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