DBMS > Hypertable vs. OrientDB vs. Qdrant vs. SQLite vs. VoltDB

System Properties Comparison Hypertable vs. OrientDB vs. Qdrant vs. SQLite vs. VoltDB

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

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

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

A high-performance vector database with neural network or semantic-based matching

Widely used embeddable, in-process RDBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Wide column store

Document store
Graph DBMS
Key-value store

Vector DBMS

Relational DBMS

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

orientdb.org

github.com/qdrant/qdrant
qdrant.tech

www.sqlite.org

www.voltdb.com

Technical documentation

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

qdrant.tech/documentation

www.sqlite.org/docs.html

docs.voltdb.com

Developer

Hypertable Inc.

OrientDB LTD; CallidusCloud; SAP

Qdrant

Dwayne Richard Hipp

VoltDB Inc.

Initial release

2009

2010

2021

2000

2010

Current release

0.9.8.11, March 2016

3.2.29, March 2024

3.45.3 (15 April 2024), April 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

Public Domain

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C++

Java

Rust

Java, C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

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

Docker
Linux
macOS
Windows

server-less

Linux
OS X

for development

Data scheme

schema-free

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

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

restricted

only exact value or prefix value scans

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

SQL-92 is not fully supported

yes

only a subset of SQL 99

APIs and other access methods

C++ API
Thrift

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java, Javascript

Java

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Multi-source replication

Collection-level replication

none

Multi-source replication
Source-replica replication

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

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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; record level security configurable

Key-based authentication

Users and roles with access to stored procedures

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