DBMS > Amazon Redshift vs. Google Cloud Spanner vs. Graphite vs. HarperDB vs. OpenTenBase

System Properties Comparison Amazon Redshift vs. Google Cloud Spanner vs. Graphite vs. HarperDB vs. OpenTenBase

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

An enterprise-level distributed HTAP open source database based on PostgreSQL

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	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.08
Rank	#370	Overall
	#156	Relational DBMS

Website

aws.amazon.com/redshift

cloud.google.com/spanner

github.com/graphite-project/graphite-web

www.harperdb.io

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

Technical documentation

docs.aws.amazon.com/redshift

cloud.google.com/spanner/docs

graphite.readthedocs.io

docs.harperdb.io/docs

docs.opentenbase.org
docs.opentenbase.org/en

Developer

Amazon (based on PostgreSQL)

Google

Chris Davis

HarperDB

OpenAtom Foundation, previously Tencent

Initial release

2012

2017

2006

2017

Current release

3.1, August 2021

2.5, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free community edition available

Open Source

BSD-3

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

Node.js

Server operating systems

hosted

Linux
Unix

Linux
OS X

Linux

Data scheme

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

JSON data types

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 data manipulation statements

yes

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
React Hooks
RESTful HTTP/JSON API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Custom Functions

since release 3.1

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

none

yes

the nodes on which a table resides can be defined

yes

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

none

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

yes

Transaction concepts

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

ACID

Strict serializable isolation

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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 and roles

Access rights for users, groups and roles according to SQL-standard

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