DBMS > BigObject vs. Google Cloud Firestore vs. Graph Engine vs. TempoIQ vs. XTDB

System Properties Comparison BigObject vs. Google Cloud Firestore vs. Graph Engine vs. TempoIQ vs. XTDB

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

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.

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Graph DBMS
Key-value store

Time Series DBMS

Document store

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	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

bigobject.io

firebase.google.com/products/firestore

www.graphengine.io

tempoiq.com (offline)

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.bigobject.io

firebase.google.com/docs/firestore

www.graphengine.io/docs/manual

www.xtdb.com/docs

Developer

BigObject, Inc.

Google

Microsoft

TempoIQ

Juxt Ltd.

Initial release

2015

2017

2010

2012

2019

Current release

1.19, September 2021

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

MIT License

commercial

Open Source

MIT License

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

.NET and C

Clojure

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

.NET

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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 DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

RESTful HTTP API

HTTP API

HTTP REST
JDBC

Supported programming languages

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

C#
C++
F#
Visual Basic

C#
Java
JavaScript

Node.js
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

Lua

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes, each node contains all data

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

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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.

simple authentication-based access control

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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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