DBMS > Apache Druid vs. Graph Engine vs. HugeGraph vs. ObjectBox vs. RocksDB

System Properties Comparison Apache Druid vs. Graph Engine vs. HugeGraph vs. ObjectBox vs. RocksDB

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A fast-speed and highly-scalable Graph DBMS

Extremely fast embedded database for small devices, IoT and Mobile

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

Primary database model

Relational DBMS
Time Series DBMS

Graph DBMS
Key-value store

Graph DBMS

Object oriented DBMS

Key-value store

Secondary database models

Time Series 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	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

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

Website

druid.apache.org

www.graphengine.io

github.com/hugegraph
hugegraph.apache.org

objectbox.io

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

www.graphengine.io/docs/manual

hugegraph.apache.org/docs

docs.objectbox.io

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Microsoft

Baidu

ObjectBox Limited

Facebook, Inc.

Initial release

2012

2010

2018

2017

2013

Current release

29.0.1, April 2024

0.9

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

MIT License

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

BSD

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

.NET and C

Java

C and C++

C++

Server operating systems

Linux
OS X
Unix

.NET

Linux
macOS
Unix

Android
iOS
Linux
macOS
Windows

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL for querying

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

Proprietary native API

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
F#
Visual Basic

Groovy
Java
Python

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

depending on used storage backend, e.g. Cassandra and HBase

online/offline synchronization between client and server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

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: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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

Users, roles and permissions

yes

More information provided by the system vendor

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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.