DBMS > atoti vs. Google Cloud Firestore vs. Kinetica vs. searchxml vs. TerarkDB

System Properties Comparison atoti vs. Google Cloud Firestore vs. Kinetica vs. searchxml vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

DBMS for structured and unstructured content wrapped with an application server

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Object oriented DBMS

Document store

Relational DBMS

Native XML DBMS
Search engine

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

atoti.io

firebase.google.com/products/firestore

www.kinetica.com

www.searchxml.net/category/products

github.com/bytedance/terarkdb

Technical documentation

docs.atoti.io

firebase.google.com/docs/firestore

docs.kinetica.com

www.searchxml.net/support/handouts

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

ActiveViam

Google

Kinetica

informationpartners gmbh

ByteDance, originally Terark

Initial release

2017

2012

2015

2016

Current release

7.1, August 2021

1.0

License

Commercial or Open Source

commercial

free versions available

commercial

restricted open source version available

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, C++

C++

Server operating systems

hosted

Linux

Windows

Data scheme

schema-free

yes

schema-free

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like DML and DDL statements

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

C++ API
Java API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

C++

most other programming languages supported via APIs

C++
Java

Server-side scripts

Stored procedures

Python

yes, Firebase Rules & Cloud Functions

user defined functions

yes

on the application server

Triggers

yes, with Cloud Functions

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

sychronisation to multiple collections

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

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.

Access rights for users and roles on table level

Domain, group and role-based access control at the document level and for application services

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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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