DBMS > Cubrid vs. EventStoreDB vs. FeatureBase vs. Google BigQuery vs. Lovefield

System Properties Comparison Cubrid vs. EventStoreDB vs. FeatureBase vs. Google BigQuery vs. Lovefield

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.

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Large scale data warehouse service with append-only tables

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Event Store

Relational 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	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

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

www.eventstore.com

www.featurebase.com

cloud.google.com/bigquery

google.github.io/lovefield

Technical documentation

cubrid.org/manuals

developers.eventstore.com

docs.featurebase.com

cloud.google.com/bigquery/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

CUBRID Corporation, CUBRID Foundation

Event Store Limited

Molecula and Pilosa Open Source Contributors

Google

Initial release

2008

2012

2017

2010

2014

Current release

11.0, January 2021

21.2, February 2021

2022, May 2022

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

JavaScript

Server operating systems

Linux
Windows

Linux
macOS

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

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 queries

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC
JDBC
Kafka Connector
ODBC

RESTful HTTP/JSON API

Supported programming languages

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

Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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