DBMS > HarperDB vs. KairosDB vs. MySQL vs. Oracle Berkeley DB vs. SAP HANA

System Properties Comparison HarperDB vs. KairosDB vs. MySQL vs. Oracle Berkeley DB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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.

Distributed Time Series DBMS based on Cassandra or H2

Widely used open source RDBMS

Widely used in-process key-value store

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

Primary database model

Document store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

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	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.harperdb.io

github.com/kairosdb/kairosdb

www.mysql.com

www.oracle.com/database/technologies/related/berkeleydb.html

www.sap.com/products/hana.html

Technical documentation

docs.harperdb.io/docs

kairosdb.github.io

dev.mysql.com/doc

docs.oracle.com/cd/E17076_05/html/index.html

help.sap.com/hana

Developer

HarperDB

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SAP

Initial release

2017

2013

1995

1994

2010

Current release

3.1, August 2021

1.2.2, November 2018

8.4.0, April 2024

18.1.40, May 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial license available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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Implementation language

Node.js

Java

C and C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
OS X

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Appliance or cloud-service

Data scheme

dynamic schema

schema-free

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

Supported programming languages

.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

Java
JavaScript

Node.js
PHP
Python

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

proprietary syntax

SQLScript, R

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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, 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

simple password-based access control

Users with fine-grained authorization concept

no user groups or roles

yes

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