DBMS > Apache Impala vs. Dgraph vs. Quasardb vs. VelocityDB

System Properties Comparison Apache Impala vs. Dgraph vs. Quasardb vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Distributed and scalable native Graph DBMS

Distributed, high-performance timeseries database

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS

Time Series DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store

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Trend Chart

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

dgraph.io/docs

doc.quasar.ai/master

velocitydb.com/UserGuide

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Dgraph Labs, Inc.

quasardb

VelocityDB Inc

Initial release

2013

2016

2009

2011

Current release

4.1.0, June 2022

3.14.1, January 2024

7.x

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

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++

Server operating systems

Linux

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Any that supports .NET

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

yes

with tags

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

HTTP API

.Net

Supported programming languages

All languages supporting JDBC/ODBC

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

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

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication via Raft

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Planned for future releases

Cryptographically strong user authentication and audit trail

Based on Windows Authentication

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More resources

Recent citations in the news

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