DBMS > HarperDB vs. Hypertable vs. OrientDB vs. SQLite

System Properties Comparison HarperDB vs. Hypertable vs. OrientDB vs. SQLite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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.

An open source BigTable implementation based on distributed file systems such as Hadoop

Multi-model DBMS (Document, Graph, Key/Value)

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Wide column store

Document store
Graph DBMS
Key-value store

Relational DBMS

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

Score	0.55
Rank	#252	Overall
	#38	Document stores

Score	3.27
Rank	#97	Overall
	#16	Document stores
	#6	Graph DBMS
	#15	Key-value stores

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

www.harperdb.io

orientdb.org

www.sqlite.org

Technical documentation

docs.harperdb.io/docs

www.orientdb.com/docs/last/index.html

www.sqlite.org/docs.html

Developer

HarperDB

Hypertable Inc.

OrientDB LTD; CallidusCloud; SAP

Dwayne Richard Hipp

Initial release

2017

2009

2010

2000

Current release

3.1, August 2021

0.9.8.11, March 2016

3.2.29, March 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

GNU version 3. Commercial license available

Open Source

Apache version 2

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Node.js

C++

Java

Server operating systems

Linux
OS X

Linux
OS X
Windows

an inofficial Windows port is available

All OS with a Java JDK (>= JDK 6)

server-less

Data scheme

dynamic schema

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON data types

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like data manipulation statements

SQL-like query language, no joins

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

C++ API
Thrift

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Java, Javascript

Triggers

Hooks

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

selectable replication factor on file system level

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Access rights for users and roles; record level security configurable

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.