DBMS > Google Cloud Datastore vs. Heroic vs. RisingWave vs. STSdb

System Properties Comparison Google Cloud Datastore vs. Heroic vs. RisingWave vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.61
Rank	#237	Overall
	#111	Relational DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

cloud.google.com/datastore

github.com/spotify/heroic

www.risingwave.com/database

github.com/STSSoft/STSdb4

Technical documentation

cloud.google.com/datastore/docs

spotify.github.io/heroic

docs.risingwave.com/docs/current/intro

Developer

Google

Spotify

RisingWave Labs

STS Soft SC

Initial release

2008

2014

2022

2011

Current release

1.2, September 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license 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

Rust

Server operating systems

hosted

Docker
Linux
macOS

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

yes

Standard SQL-types and JSON

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

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
PostgreSQL wire protocol

.NET Client API

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

using Google App Engine

UDFs in Python or Java

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users and Roles

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