DBMS > Apache IoTDB vs. Google Cloud Firestore vs. TimesTen vs. XTDB

System Properties Comparison Apache IoTDB vs. Google Cloud Firestore vs. TimesTen vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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.

In-Memory RDBMS compatible to Oracle

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

Primary database model

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

iotdb.apache.org

firebase.google.com/products/firestore

www.oracle.com/database/technologies/related/timesten.html

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

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

firebase.google.com/docs/firestore

docs.oracle.com/database/timesten-18.1

www.xtdb.com/docs

Developer

Apache Software Foundation

Google

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Juxt Ltd.

Initial release

2018

2017

1998

2019

Current release

1.1.0, April 2023

11 Release 2 (11.2.2.8.0)

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

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

Clojure

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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 query language

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
Native API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST
JDBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

C
C++
Java
PL/SQL

Clojure
Java

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

PL/SQL

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Multi-source replication

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

yes

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

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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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