DBMS > Couchbase vs. Dgraph vs. HarperDB vs. MySQL vs. SAP HANA

System Properties Comparison Couchbase vs. Dgraph vs. HarperDB vs. MySQL vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Distributed and scalable native Graph DBMS

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.

Widely used open source RDBMS

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.sap.com/products/hana.html

Technical documentation

docs.couchbase.com

dgraph.io/docs

docs.harperdb.io/docs

dev.mysql.com/doc

help.sap.com/hana

Developer

Couchbase, Inc.

Dgraph Labs, Inc.

HarperDB

Oracle

since 2010, originally MySQL AB, then Sun

SAP

Initial release

2011

2016

2017

1995

2010

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.1, August 2021

8.4.0, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

commercial

free community edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Go and Erlang

Node.js

C and C++

Server operating systems

Linux
OS X
Windows

Linux
OS X

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

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

Secondary indexes

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like data manipulation statements

yes

with proprietary extensions

yes

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C#
C++
Go
Java
JavaScript (Node.js)
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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Custom Functions

since release 3.1

yes

proprietary syntax

SQLScript, R

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

yes

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Synchronous replication via Raft

yes

the nodes on which a table resides can be defined

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Planned for future releases

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

yes

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