DBMS > Apache Drill vs. BigObject vs. Graph Engine vs. Valentina Server

System Properties Comparison Apache Drill vs. BigObject vs. Graph Engine vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Analytic DBMS for real-time computations and queries

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Object-relational database and reports server

Primary database model

Document store
Relational DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Graph DBMS
Key-value store

Relational DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

Technical documentation

drill.apache.org/docs

docs.bigobject.io

www.graphengine.io/docs/manual

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Apache Software Foundation

BigObject, Inc.

Microsoft

Paradigma Software

Initial release

2012

2015

2010

1999

Current release

1.20.3, January 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free community edition available

Open Source

MIT License

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

.NET and C

Server operating systems

Linux
OS X
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

.NET

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

ODBC

Supported programming languages

C++

C#
C++
F#
Visual Basic

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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More resources

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13 February 2017, InfoWorld

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