DBMS > Geode vs. Google BigQuery vs. H2 vs. VoltDB

System Properties Comparison Geode vs. Google BigQuery vs. H2 vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Large scale data warehouse service with append-only tables

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

geode.apache.org

cloud.google.com/bigquery

www.h2database.com

www.voltdb.com

Technical documentation

geode.apache.org/docs

cloud.google.com/bigquery/docs

www.h2database.com/html/main.html

docs.voltdb.com

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Google

Thomas Mueller

VoltDB Inc.

Initial release

2002

2010

2005

2010

Current release

1.1, February 2017

2.2.220, July 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

hosted

All OS with a Java VM

Linux
OS X

for development

Data scheme

schema-free

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

SQL-like query language (OQL)

yes

only a subset of SQL 99

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java Stored Procedures and User-Defined Functions

Java

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes, on a single node

Since BigQuery is designed for querying data

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Access rights per client and object definable

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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