DBMS > Axibase vs. FatDB vs. Google Cloud Firestore vs. Typesense vs. Yaacomo

System Properties Comparison Axibase vs. FatDB vs. Google Cloud Firestore vs. Typesense vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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 typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Document store
Key-value store

Document store

Search engine

Relational DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

axibase.com/docs/atsd/finance

firebase.google.com/products/firestore

typesense.org

yaacomo.com

Technical documentation

firebase.google.com/docs/firestore

typesense.org/docs

Developer

Axibase Corporation

FatCloud

Google

Q2WEB GmbH

Initial release

2013

2012

2017

2015

2009

Current release

15585

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

GPL V3

commercial

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

Windows

hosted

Linux

Android
Linux
Windows

Data scheme

yes

schema-free

pre-defined schema optional

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

Via inetgration in SQL Server

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

yes

via applications

yes, Firebase Rules & Cloud Functions

Triggers

yes

via applications

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Multi-source replication

Multi-source replication using RAFT

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

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

In-memory capabilities

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

yes

User concepts

Access control

Can implement custom security layer via applications

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

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