DBMS > GeoSpock vs. Google BigQuery vs. NSDb vs. StarRocks vs. SwayDB

System Properties Comparison GeoSpock vs. Google BigQuery vs. NSDb vs. StarRocks vs. SwayDB

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

geospock.com

cloud.google.com/bigquery

nsdb.io

www.starrocks.io

swaydb.simer.au

Technical documentation

cloud.google.com/bigquery/docs

nsdb.io/Architecture

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

GeoSpock

Google

The Linux Foundation

since Feb 2023

Simer Plaha

Initial release

2010

2017

2020

2018

Current release

2.0, September 2019

2.5.3, March 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

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

Java, Javascript

Java, Scala

C++, Java

Scala

Server operating systems

hosted

Linux
macOS

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

temporal, categorical

all fields are automatically indexed

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

SQL-like query language

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

gRPC
HTTP REST
WebSocket

JDBC
MySQL protocol

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
Scala

Java

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

horizontal partitioning (by range and hash)

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

Eventual Consistency

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

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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)

Role based access control and fine grained access rights

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