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

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

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

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

Graph DBMS
Relational DBMS

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	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

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

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

bitnine.net/agensgraph

druid.apache.org

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

rocksdb.org

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

Technical documentation

bitnine.net/documentation

druid.apache.org/docs/latest/design

docs.databend.com

github.com/facebook/rocksdb/wiki

Developer

Bitnine Global Inc.

Apache Software Foundation and contributors

Databend Labs

Facebook, Inc.

Initial release

2016

2012

2021

2013

2009

Current release

2.1, December 2018

29.0.1, April 2024

1.0.59, April 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache license v2

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Rust

C++

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix

hosted
Linux
macOS

Linux

Data scheme

depending on used data model

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

yes

SQL for querying

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC
RESTful HTTP/JSON API

CLI Client
JDBC
RESTful HTTP API

C++ API
Java API

TinkerPop 3

Supported programming languages

C
Java
JavaScript
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python
Rust

C
C++
Go
Java
Perl
Python
Ruby

Groovy
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

manual/auto, time-based

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, via HDFS, S3 or other storage engines

none

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

ACID

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

fine grained access rights according to SQL-standard

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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