DBMS > ClickHouse vs. NebulaGraph vs. QuestDB vs. Riak TS vs. Spark SQL

System Properties Comparison ClickHouse vs. NebulaGraph vs. QuestDB vs. Riak TS vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

A distributed, linear scalable, high perfomant Graph DBMS

A high performance open source SQL database for time series data

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	2.14
Rank	#120	Overall
	#10	Graph DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

clickhouse.com

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

questdb.io

spark.apache.org/sql

Technical documentation

clickhouse.com/docs

docs.nebula-graph.io

questdb.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Clickhouse Inc.

Vesoft Inc.

QuestDB Technology Inc

Open Source, formerly Basho Technologies

Apache Software Foundation

Initial release

2016

2019

2014

2015

2014

Current release

v24.4.1.2088-stable, May 2024

3.0.0, September 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0 + Common Clause 1.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java (Zero-GC), C++, Rust

Erlang

Scala

Server operating systems

FreeBSD
Linux
macOS

Linux

Linux
macOS
Windows

Linux
OS X

Linux
OS X
Windows

Data scheme

yes

Strong typed schema

yes

schema-free via InfluxDB Line Protocol

schema-free

yes

Typing

predefined data types such as float or date

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

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.

restricted

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

SQL with time-series extensions

yes, limited

SQL-like DML and DDL statements

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

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

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

.Net
C++
Go
Java
PHP
Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

horizontal partitioning (by timestamps)

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Causal Clustering using Raft protocol

Source-replica replication with eventual consistency

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

links between datasets can be stored

Transaction concepts

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

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

In-memory capabilities

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

yes

through memory mapped files

User concepts

Access control

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Role-based access control

More information provided by the system vendor

Specific characteristics

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

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

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

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

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

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

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

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Market metrics

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

Licensing and pricing models

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

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.