DBMS > BigObject vs. EsgynDB vs. OpenQM vs. QuestDB

System Properties Comparison BigObject vs. EsgynDB vs. OpenQM vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

QpenQM is a high-performance, self-tuning, multi-value DBMS

A high performance open source SQL database for time series data

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Multivalue DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Website

bigobject.io

www.esgyn.cn

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

questdb.io

Technical documentation

docs.bigobject.io

questdb.io/docs

Developer

BigObject, Inc.

Esgyn

Rocket Software, originally Martin Phillips

QuestDB Technology Inc

Initial release

2015

1993

2014

Current release

3.4-12

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

with some exceptions

yes

schema-free via InfluxDB Line Protocol

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

SQL-like DML and DDL statements

yes

SQL with time-series extensions

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

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

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
Basic
C
Java
Objective C
PHP
Python

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

over HTTP

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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

Fluid real-time dashboards with Grafana and QuestDB
11 June 2024

QuestDB 8.0: Major Release
23 May 2024

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

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

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More resources

Recent citations in the news

QuestDB snares $12M Series A with hosted version coming soon
3 November 2021, TechCrunch

SQL Extensions for Time-Series Data in QuestDB
11 January 2021, Towards Data Science

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

QuestDB Raises $12M in Series A Funding
8 November 2021, FinSMEs

Aquis Exchange goes live with QuestDB for real time monitoring
2 November 2022, FinanceFeeds

provided by Google News

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