DBMS > Cubrid vs. EventStoreDB vs. Graphite vs. HEAVY.AI vs. RocksDB

System Properties Comparison Cubrid vs. EventStoreDB vs. Graphite vs. HEAVY.AI vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

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

Website

cubrid.com (korean)
cubrid.org (english)

www.eventstore.com

github.com/graphite-project/graphite-web

github.com/heavyai/heavydb
www.heavy.ai

rocksdb.org

Technical documentation

cubrid.org/manuals

developers.eventstore.com

graphite.readthedocs.io

docs.heavy.ai

github.com/facebook/rocksdb/wiki

Developer

CUBRID Corporation, CUBRID Foundation

Event Store Limited

Chris Davis

HEAVY.AI, Inc.

Facebook, Inc.

Initial release

2008

2012

2006

2016

2013

Current release

11.0, January 2021

21.2, February 2021

5.10, January 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition 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

C, C++, Java

Python

C++ and CUDA

C++

Server operating systems

Linux
Windows

Linux
Unix

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

HTTP API
Sockets

JDBC
ODBC
Thrift
Vega

C++ API
Java API

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

locking

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

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