DBMS > Cubrid vs. GeoMesa vs. Google BigQuery vs. Graph Engine vs. InfluxDB

System Properties Comparison Cubrid vs. GeoMesa vs. Google BigQuery vs. Graph Engine vs. InfluxDB

Editorial information provided by DB-Engines

Name

Description

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Large scale data warehouse service with append-only tables

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

DBMS for storing time series, events and metrics

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Website

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

www.geomesa.org

cloud.google.com/bigquery

www.graphengine.io

www.influxdata.com/products/influxdb-overview

Technical documentation

cubrid.org/manuals

www.geomesa.org/documentation/stable/user/index.html

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

docs.influxdata.com/influxdb

Developer

CUBRID Corporation, CUBRID Foundation

CCRi and others

Google

Microsoft

Initial release

2008

2014

2010

2013

Current release

11.0, January 2021

4.0.5, February 2024

2.7.6, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

commercial

Open Source

MIT License

Open Source

MIT-License; commercial enterprise version available

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

Scala

.NET and C

Server operating systems

Linux
Windows

hosted

.NET

Linux
OS X

through Homebrew

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

RESTful HTTP API

HTTP API
JSON over UDP

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
F#
Visual Basic

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

horizontal partitioning

Sharding

in enterprise version only

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

selectable replication factor

in enterprise version only

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Since BigQuery is designed for querying data

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.

depending on storage layer

yes

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

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

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

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