DBMS > GreptimeDB vs. Microsoft Azure SQL Database vs. NebulaGraph vs. NSDb vs. OrigoDB

System Properties Comparison GreptimeDB vs. Microsoft Azure SQL Database vs. NebulaGraph vs. NSDb vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Database as a Service offering with high compatibility to Microsoft SQL Server

A distributed, linear scalable, high perfomant Graph DBMS

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

A fully ACID in-memory object graph database

Primary database model

Document store
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	2.23
Rank	#116	Overall
	#10	Graph DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

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

Website

greptime.com

azure.microsoft.com/en-us/products/azure-sql/database

github.com/vesoft-inc/nebula
www.nebula-graph.io

nsdb.io

origodb.com

Technical documentation

docs.greptime.com

docs.microsoft.com/en-us/azure/azure-sql

docs.nebula-graph.io

nsdb.io/Architecture

origodb.com/docs

Developer

Greptime Inc.

Microsoft

Vesoft Inc.

Robert Friberg et al

Initial release

2022

2010

2019

2017

2009

under the name LiveDB

Current release

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0 + Common Clause 1.0

Open Source

Apache Version 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

C++

Java, Scala

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

hosted

Linux

Linux
macOS

Linux
Windows

Data scheme

schema-free, schema definition possible

yes

Strong typed schema

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

gRPC
HTTP API
JDBC

ADO.NET
JDBC
ODBC

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Supported programming languages

C++
Erlang
Go
Java
JavaScript

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C++
Go
Java
PHP
Python

Java
Scala

.Net

Server-side scripts

Stored procedures

Python

Transact SQL

user defined functions

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

Causal Clustering using Raft protocol

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

Foreign keys

Referential integrity

yes

Relationships in graphs

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

Using Apache Lucene

yes

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

Simple rights management via user accounts

fine grained access rights according to SQL-standard

Role-based access control

Role based authorization

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

NebulaGraph boasts the world's only graph database solution that is able to host...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Companies from a variety of industries have implemented NebulaGraph Database in production,...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

At our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

NebulaGraph is open source and free to use under Apache 2.0 license.
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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