DBMS > Faircom DB vs. QuestDB vs. TerarkDB vs. XTDB

System Properties Comparison Faircom DB vs. QuestDB vs. TerarkDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A high performance open source SQL database for time series data

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Key-value store

Document store

Secondary database models

Relational DBMS

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

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

www.faircom.com/products/faircom-db

questdb.io

github.com/bytedance/terarkdb

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

questdb.io/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

www.xtdb.com/docs

Developer

FairCom Corporation

QuestDB Technology Inc

ByteDance, originally Terark

Juxt Ltd.

Initial release

1979

2014

2016

2019

Current release

V13, July 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

restricted open source version available

Open Source

MIT License

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

ANSI C, C++

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

C++

Clojure

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
macOS
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema free, schema optional, schema required, partial schema,

yes

schema-free via InfluxDB Line Protocol

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

yes, extensible-data-notation format

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, ANSI SQL with proprietary extensions

SQL with time-series extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

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

C++ API
Java API

HTTP REST
JDBC

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

over HTTP

C++
Java

Clojure
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

horizontal partitioning (by timestamps)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication with eventual consistency

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

through memory mapped files

yes

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

More information provided by the system vendor

News

Combine Java and Rust Code Coverage in a Polyglot Project
10 September 2024

Weather data visualization and forecasting with QuestDB, Kafka and Grafana
4 September 2024

Building a new vector based storage model
22 August 2024

Calibrating VWAP executions with QuestDB and Grafana
16 August 2024

Write Time: a call for community writers
13 August 2024

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More resources

Recent citations in the news

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

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

QuestDB gets $12M Series A funding amid growing interest in time-series databases
3 November 2021, SiliconANGLE News

Read the Pitch Deck Database Startup QuestDB Used to Raise $12 Million
11 November 2021, Business Insider

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

provided by Google News

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