DBMS > Amazon DynamoDB vs. GBase vs. HarperDB vs. MarkLogic vs. Newts

System Properties Comparison Amazon DynamoDB vs. GBase vs. HarperDB vs. MarkLogic vs. Newts

Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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.

Operational and transactional Enterprise NoSQL database

Time Series DBMS based on Cassandra

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Time Series DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.gbase.cn

www.harperdb.io

www.progress.com/marklogic

opennms.github.io/newts

Technical documentation

docs.aws.amazon.com/dynamodb

docs.harperdb.io/docs

www.progress.com/marklogic/documentation

github.com/OpenNMS/newts/wiki

Developer

Amazon

General Data Technology Co., Ltd.

HarperDB

MarkLogic Corp.

OpenNMS Group

Initial release

2012

2004

2017

2001

2014

Current release

GBase 8a, GBase 8s, GBase 8c

3.1, August 2021

11.0, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free community edition available

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, Python

Node.js

C++

Java

Server operating systems

hosted

Linux

Linux
OS X

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic schema

schema-free

Schema can be enforced

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like data manipulation statements

yes

SQL92

APIs and other access methods

RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

HTTP REST
Java API

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
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

user defined functions

Custom Functions

since release 3.1

yes

via XQuery or JavaScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

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

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

yes

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

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

ACID

Atomic execution of specific operations

ACID

can act as a resource manager in an XA/JTA transaction

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

yes, with Range Indexes

User concepts

Access control

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

yes

Access rights for users and roles

Role-based access control at the document and subdocument levels

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