DBMS > chDB vs. Google Cloud Firestore vs. LeanXcale vs. Titan

System Properties Comparison chDB vs. Google Cloud Firestore vs. LeanXcale vs. Titan

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Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

An embedded SQL OLAP Engine powered by ClickHouse

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 highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

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

Score	0.05
Rank	#358	Overall
	#152	Relational DBMS

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Website

github.com/chdb-io/chdb

firebase.google.com/products/firestore

www.leanxcale.com

github.com/thinkaurelius/titan

Technical documentation

doc.chdb.io

firebase.google.com/docs/firestore

github.com/thinkaurelius/titan/wiki

Developer

Google

LeanXcale

Aurelius, owned by DataStax

Initial release

2023

2017

2015

2012

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache license, version 2.0

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

Server operating systems

server-less

hosted

Linux
OS X
Unix
Windows

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

Close to ANSI SQL (SQL/JSON + extensions)

yes

through Apache Derby

APIs and other access methods

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

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

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

C
Java
Scala

Clojure
Java
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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.

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

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

show all

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

Realtime vs Cloud Firestore: Which Firebase Database to Choose
8 March 2024, Appinventiv

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google launches Firebase Genkit, a new open source framework for building AI-powered apps
14 May 2024, TechCrunch

NoSQL on the Cloud With Python
7 August 2020, Towards Data Science

Google Launches Cloud NoSQL Database for Mobile, Web Apps
10 October 2017, ADT Magazine

provided by Google News

DataStax Acquires Aurelius and its TitanDB Graph Database
31 May 2024, Data Center Knowledge

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database
24 August 2015, AWS Blog

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

Database Deep Dives: JanusGraph
8 August 2019, IBM

provided by Google News

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