DBMS > GeoSpock vs. Google BigQuery vs. RisingWave vs. TerarkDB

System Properties Comparison GeoSpock vs. Google BigQuery vs. RisingWave vs. TerarkDB

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Large scale data warehouse service with append-only tables

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

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

Key-value store

Secondary database models

Time Series DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

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

Website

geospock.com

cloud.google.com/bigquery

www.risingwave.com/database

github.com/bytedance/terarkdb

Technical documentation

cloud.google.com/bigquery/docs

docs.risingwave.com/docs/current/intro

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

GeoSpock

Google

RisingWave Labs

ByteDance, originally Terark

Initial release

2010

2022

2016

Current release

2.0, September 2019

1.2, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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, Javascript

Rust

C++

Server operating systems

hosted

Docker
Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

JDBC
PostgreSQL wire protocol

C++ API
Java API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

UDFs in Python or Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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 rights for users can be defined per table

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

Google Cloud Identity & Access Management (IAM)

Users and Roles

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