DBMS > NSDb vs. OrigoDB vs. VictoriaMetrics vs. Vitess

System Properties Comparison NSDb vs. OrigoDB vs. VictoriaMetrics vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

Technical documentation

nsdb.io/Architecture

origodb.com/docs

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

vitess.io/docs

Developer

Robert Friberg et al

VictoriaMetrics

The Linux Foundation, PlanetScale

Initial release

2017

2009

under the name LiveDB

2018

2013

Current release

v1.91, May 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0, commercial licenses available

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, Scala

Server operating systems

Linux
macOS

Linux
Windows

FreeBSD
Linux
macOS
OpenBSD

Docker
Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java
Scala

.Net

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication

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

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

depending on model

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

Using Apache Lucene

yes

Write ahead log

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

Role based authorization

Users with fine-grained authorization concept

no user groups or roles

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More resources

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