DBMS > Amazon Neptune vs. HarperDB vs. OpenEdge vs. Vertica vs. Yanza

System Properties Comparison Amazon Neptune vs. HarperDB vs. OpenEdge vs. Vertica vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Fast, reliable graph database built for the cloud

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

Application development environment with integrated database management system

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Time Series DBMS for IoT Applications

Primary database model

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

aws.amazon.com/neptune

www.harperdb.io

www.progress.com/openedge

www.vertica.com

yanza.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.harperdb.io/docs

documentation.progress.com/output/ua/OpenEdge_latest

vertica.com/documentation

Developer

Amazon

HarperDB

Progress Software Corporation

OpenText

previously Micro Focus and Hewlett Packard

Yanza

Initial release

2017

1984

2005

2015

Current release

3.1, August 2021

OpenEdge 12.2, March 2020

12.0.3, January 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

Limited community edition free

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

but mainly used as a service provided by Yanza

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

AIX
HP-UX
Linux
Solaris
Windows

Linux

Windows

Data scheme

schema-free

dynamic schema

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like data manipulation statements

yes

close to SQL 92

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.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

Progress proprietary ABL (Advanced Business Language)

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

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

horizontal partitioning

since Version 11.4

horizontal partitioning, hierarchical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

yes

the nodes on which a table resides can be defined

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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

Users and groups

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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