DBMS > Amazon Redshift vs. Axibase vs. Google Cloud Firestore vs. Kyligence Enterprise vs. RavenDB

System Properties Comparison Amazon Redshift vs. Axibase vs. Google Cloud Firestore vs. Kyligence Enterprise vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

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 analytics engine for big data, built on top of Apache Kylin

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

aws.amazon.com/redshift

axibase.com/docs/atsd/finance

firebase.google.com/products/firestore

kyligence.io/kyligence-enterprise

ravendb.net

Technical documentation

docs.aws.amazon.com/redshift

firebase.google.com/docs/firestore

ravendb.net/docs

Developer

Amazon (based on PostgreSQL)

Axibase Corporation

Google

Kyligence, Inc.

Hibernating Rhinos

Initial release

2012

2013

2017

2016

2010

Current release

15585

5.4, July 2022

License

Commercial or Open Source

commercial

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

commercial

Open Source

AGPL version 3, commercial license available

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

Server operating systems

hosted

Linux

hosted

Linux

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

ANSI SQL for queries (using Apache Calcite)

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

JDBC
ODBC
RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

yes

ACID, Cluster-wide transaction available

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

fine grained access rights according to SQL-standard

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

Authorization levels configured per client per database

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