DBMS > Apache Drill vs. BigchainDB vs. Oracle Berkeley DB vs. SurrealDB vs. VoltDB

System Properties Comparison Apache Drill vs. BigchainDB vs. Oracle Berkeley DB vs. SurrealDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Widely used in-process key-value store

A fully ACID transactional, developer-friendly, multi-model DBMS

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

Document store
Relational DBMS

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Graph DBMS

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	0.85
Rank	#208	Overall
	#35	Document stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

drill.apache.org

www.bigchaindb.com

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

surrealdb.com

www.voltdb.com

Technical documentation

drill.apache.org/docs

bigchaindb.readthedocs.io/en/latest

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

surrealdb.com/docs

docs.voltdb.com

Developer

Apache Software Foundation

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SurrealDB Ltd

VoltDB Inc.

Initial release

2012

2016

1994

2022

2010

Current release

1.20.3, January 2023

18.1.40, May 2020

v1.5.0, May 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL v3

Open Source

commercial license available

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

Python

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

Rust

Java, C++

Server operating systems

Linux
OS X
Windows

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS
Windows

Linux
OS X

for development

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

SQL interfaced based on SQLite is available

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

CLI Client
RESTful HTTP API

GraphQL
RESTful HTTP API
WebSocket

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++

Go
Haskell
Java
JavaScript
Python
Ruby

.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

Deno
Go
JavaScript (Node.js)
Rust

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java

Triggers

yes

only for the SQL API

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

Source-replica replication

Multi-source replication
Source-replica replication

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

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

Data access is serialized by the server

Durability

Support for making data persistent

Depending on the underlying data source

yes,with MongoDB ord RethinkDB

yes

Snapshots and command logging

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

yes

yes, based on authentication and database rules

Users and roles with access to stored procedures

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