DBMS > Amazon Redshift vs. Google Cloud Spanner vs. Graphite vs. Hive vs. WakandaDB

System Properties Comparison Amazon Redshift vs. Google Cloud Spanner vs. Graphite vs. Hive vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

data warehouse software for querying and managing large distributed datasets, built on Hadoop

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

aws.amazon.com/redshift

cloud.google.com/spanner

github.com/graphite-project/graphite-web

hive.apache.org

wakanda.github.io

Technical documentation

docs.aws.amazon.com/redshift

cloud.google.com/spanner/docs

graphite.readthedocs.io

cwiki.apache.org/confluence/display/Hive/Home

wakanda.github.io/doc

Developer

Amazon (based on PostgreSQL)

Google

Chris Davis

Apache Software Foundation

initially developed by Facebook

Wakanda SAS

Initial release

2012

2017

2006

2012

Current release

3.1.3, April 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

AGPLv3, extended 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

Python

Java

C++, JavaScript

Server operating systems

hosted

Linux
Unix

All OS with a Java VM

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

Query statements complying to ANSI 2011

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
Sockets

JDBC
ODBC
Thrift

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C++
Java
PHP
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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

fine grained access rights according to SQL-standard

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

Access rights for users, groups and roles

yes

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