DBMS > Google BigQuery vs. ObjectBox vs. QuestDB vs. SQream DB vs. Trafodion

System Properties Comparison Google BigQuery vs. ObjectBox vs. QuestDB vs. SQream DB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

Extremely fast embedded database for small devices, IoT and Mobile

A high performance open source SQL database for time series data

a GPU-based, columnar RDBMS for big data analytics workloads

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

cloud.google.com/bigquery

Technical documentation

cloud.google.com/bigquery/docs

docs.objectbox.io

questdb.io/docs

docs.sqream.com

trafodion.apache.org/documentation.html

Developer

Google

ObjectBox Limited

QuestDB Technology Inc

SQream Technologies

Apache Software Foundation, originally developed by HP

Initial release

2010

2017

2014

2017

2014

Current release

2022.1.6, December 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

Open Source

Apache 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.

Implementation language

C and C++

Java (Zero-GC), C++, Rust

C++, CUDA, Haskell, Java, Scala

C++, Java

Server operating systems

hosted

Android
iOS
Linux
macOS
Windows

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free via InfluxDB Line Protocol

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

yes

SQL with time-series extensions

yes

APIs and other access methods

RESTful HTTP/JSON API

Proprietary native API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

.Net
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

C++
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions in Python

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by timestamps)

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

online/offline synchronization between client and server

Source-replica replication with eventual consistency

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

ACID for single-table writes

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

through memory mapped files

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

QuestDB and Raspberry Pi 5 benchmark, a pocket-sized powerhouse
8 May 2024

Build your own resource monitor with QuestDB and Grafana
6 May 2024

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

Create an ADS-B flight radar with QuestDB and a Raspberry Pi
8 April 2024

Build a temperature IoT sensor with Raspberry Pi Pico & QuestDB
5 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.