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

System Properties Comparison Apache Druid vs. Graph Engine vs. ObjectBox vs. OceanBase 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

Extremely fast embedded database for small devices, IoT and Mobile

A distributed, high available RDBMS compatible with Oracle and MySQL

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

Object oriented DBMS

Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

Document store
Wide column store

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	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	1.57
Rank	#149	Overall
	#69	Relational DBMS

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

Website

Technical documentation

druid.apache.org/docs/latest/design

www.graphengine.io/docs/manual

docs.objectbox.io

en.oceanbase.com/docs/oceanbase-database

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Microsoft

ObjectBox Limited

OceanBase

previously Alibaba and Ant Group

Facebook, Inc.

Initial release

2012

2010

2017

2010

2013

Current release

29.0.1, April 2024

4.3.0, April 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

MIT License

Open Source

Apache License 2.0

Open Source

Commercial license available

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

C and C++

C++

Server operating systems

Linux
OS X
Unix

.NET

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
F#
Visual Basic

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

none

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

online/offline synchronization between client and server

Multi-source replication using Paxos

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

yes

Access rights for users, groups and roles according to SQL-standard

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