DBMS > Apache Druid vs. Databend vs. Firebolt vs. RocksDB vs. TinkerGraph

System Properties Comparison Apache Druid vs. Databend vs. Firebolt vs. RocksDB vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Graph DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

druid.apache.org

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

www.firebolt.io

rocksdb.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

druid.apache.org/docs/latest/design

docs.databend.com

docs.firebolt.io

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Databend Labs

Firebolt Analytics Inc.

Facebook, Inc.

Initial release

2012

2021

2020

2013

2009

Current release

29.0.1, April 2024

1.0.59, April 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

Open Source

BSD

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Rust

C++

Java

Server operating systems

Linux
OS X
Unix

hosted
Linux
macOS

hosted

Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

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

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
JDBC
RESTful HTTP API

.Net
ODBC
RESTful HTTP API

C++ API
Java API

TinkerPop 3

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python
Rust

Go
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Groovy
Java

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

depending on storage layer

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users with fine-grained authorization concept, user roles

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