DBMS > EXASOL vs. Google BigQuery vs. Google Cloud Firestore vs. Hazelcast vs. TerarkDB

System Properties Comparison EXASOL vs. Google BigQuery vs. Google Cloud Firestore vs. Hazelcast vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Large scale data warehouse service with append-only tables

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 widely adopted in-memory data grid

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

Relational DBMS

Document store

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

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

Website

www.exasol.com

cloud.google.com/bigquery

firebase.google.com/products/firestore

hazelcast.com

github.com/bytedance/terarkdb

Technical documentation

www.exasol.com/resources

cloud.google.com/bigquery/docs

firebase.google.com/docs/firestore

hazelcast.org/imdg/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Exasol

Google

Hazelcast

ByteDance, originally Terark

Initial release

2000

2010

2017

2008

2016

Current release

5.3.6, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses 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++

Server operating systems

hosted

All OS with a Java VM

Data scheme

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

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

JCache
JPA
Memcached protocol
RESTful HTTP API

C++ API
Java API

Supported programming languages

Java
Lua
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes, Firebase Rules & Cloud Functions

yes

Event Listeners, Executor Services

Triggers

yes

yes, with Cloud Functions

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Replicated Map

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

yes

one or two-phase-commit; repeatable reads; read commited

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

Access rights for users, groups and roles according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.