DBMS > Databend vs. Google Cloud Firestore vs. Kinetica vs. Kingbase vs. OpenSearch

System Properties Comparison Databend vs. Google Cloud Firestore vs. Kinetica vs. Kingbase vs. OpenSearch

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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.

Fully vectorized database across both GPUs and CPUs

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

Vector DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Website

github.com/datafuselabs/databend
www.databend.com

firebase.google.com/products/firestore

www.kinetica.com

www.kingbase.com.cn

github.com/opensearch-project
opensearch.org

Technical documentation

docs.databend.com

firebase.google.com/docs/firestore

docs.kinetica.com

opensearch.org/docs/latest

Developer

Databend Labs

Google

Kinetica

BeiJing KINGBASE Information technologies inc.

Amazon Web Services

Initial release

2021

2017

2012

1999

2021

Current release

1.0.59, April 2023

7.1, August 2021

V8.0, August 2021

2.5.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 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.

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Implementation language

Rust

C, C++

C and Java

Java

Server operating systems

hosted
Linux
macOS

hosted

Linux

Linux
Windows

All OS with a Java VM

Data scheme

yes

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

SQL-like DML and DDL statements

Standard with numerous extensions

SQL-like query language

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

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

JDBC
ODBC
RESTful HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Java API
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

yes

Triggers

yes, with Cloud Functions

yes

triggers when inserted values for one or more columns fall within a specified range

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

GPU vRAM or System RAM

User concepts

Access control

Users with fine-grained authorization concept, user roles

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

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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