DBMS > Google BigQuery vs. ReductStore vs. STSdb vs. TerarkDB

System Properties Comparison Google BigQuery vs. ReductStore vs. STSdb vs. TerarkDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Time Series DBMS

Key-value store

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

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

Website

cloud.google.com/bigquery

github.com/reductstore
www.reduct.store

github.com/STSSoft/STSdb4

github.com/bytedance/terarkdb

Technical documentation

cloud.google.com/bigquery/docs

www.reduct.store/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Google

ReductStore LLC

STS Soft SC

ByteDance, originally Terark

Initial release

2010

2023

2011

2016

Current release

1.9, March 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

Open Source

GPLv2, commercial license 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

C++, Rust

C++

Server operating systems

hosted

Docker
Linux
macOS
Windows

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API

.NET Client API

C++ API
Java API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
JavaScript (Node.js)
Python
Rust

C#
Java

C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

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

Google Cloud Identity & Access Management (IAM)

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.