DBMS > BigObject vs. Google Cloud Firestore vs. Ingres vs. SiriDB vs. VoltDB

System Properties Comparison BigObject vs. Google Cloud Firestore vs. Ingres vs. SiriDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Well established RDBMS

Open Source Time Series DBMS

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

Relational DBMS

a hierachical model (tree) can be imposed

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	3.63
Rank	#79	Overall
	#43	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

bigobject.io

firebase.google.com/products/firestore

www.actian.com/databases/ingres

siridb.com

www.voltdb.com

Technical documentation

docs.bigobject.io

firebase.google.com/docs/firestore

docs.actian.com/ingres

docs.siridb.com

docs.voltdb.com

Developer

BigObject, Inc.

Google

Actian Corporation

Cesbit

VoltDB Inc.

Initial release

2015

2017

1974

originally developed at University Berkely in early 1970s

2017

2010

Current release

12.0, July 2024

11.3, April 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

MIT 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

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

Implementation language

Java, C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Linux
OS X

for development

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

yes, Firebase Rules & Cloud Functions

yes

Java

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Ingres Replicator

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

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 for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

simple rights management via user accounts

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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