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

System Properties Comparison Amazon DynamoDB vs. GBase vs. HarperDB vs. NCache 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.

Open-Source and Enterprise in-memory Key-Value Store

Time Series DBMS based on Cassandra

Primary database model

Document store
Key-value store

Secondary database models

Document store
Search engine

Using distributed Lucene

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	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.gbase.cn

www.harperdb.io

www.alachisoft.com/ncache

opennms.github.io/newts

Technical documentation

docs.aws.amazon.com/dynamodb

docs.harperdb.io/docs

www.alachisoft.com/resources/docs

github.com/OpenNMS/newts/wiki

Developer

Amazon

General Data Technology Co., Ltd.

HarperDB

Alachisoft

OpenNMS Group

Initial release

2012

2004

2017

2005

2014

Current release

GBase 8a, GBase 8s, GBase 8c

3.1, August 2021

5.3.3, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free community edition available

Open Source

Enterprise Edition available

Open Source

Apache 2.0

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

C, Java, Python

Node.js

C#, .NET, .NET Core, Java

Java

Server operating systems

hosted

Linux

Linux
OS X

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

IDistributedCache
JCache
LINQ
Proprietary native API

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Java

Server-side scripts

Stored procedures

user defined functions

Custom Functions

since release 3.1

support for stored procedures with SQL-Server CLR

Triggers

yes

by integration with AWS Lambda

yes

Notifications

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

yes

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, with selectable consistency level

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

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

optimistic locking and pessimistic locking

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)

yes

Access rights for users and roles

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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