DBMS > Amazon DynamoDB vs. HarperDB vs. Microsoft Azure Synapse Analytics vs. Postgres-XL

System Properties Comparison Amazon DynamoDB vs. HarperDB vs. Microsoft Azure Synapse Analytics vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

aws.amazon.com/dynamodb

www.harperdb.io

azure.microsoft.com/services/synapse-analytics

www.postgres-xl.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.harperdb.io/docs

docs.microsoft.com/azure/synapse-analytics

www.postgres-xl.org/documentation

Developer

Amazon

HarperDB

Microsoft

Initial release

2012

2017

2016

2014

since 2012, originally named StormDB

Current release

3.1, August 2021

10 R1, October 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free community edition available

commercial

Open Source

Mozilla public license

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

Node.js

C++

Server operating systems

hosted

Linux
OS X

hosted

Linux
macOS

Data scheme

schema-free

dynamic schema

yes

Typing

predefined data types such as float or date

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.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#
Java
PHP

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Transact SQL

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Atomic execution of specific operations

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

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