DBMS > BoltDB vs. Couchbase vs. HugeGraph vs. Microsoft Access vs. RocksDB

System Properties Comparison BoltDB vs. Couchbase vs. HugeGraph vs. Microsoft Access vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A fast-speed and highly-scalable Graph DBMS

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

github.com/boltdb/bolt

www.couchbase.com

github.com/hugegraph
hugegraph.apache.org

www.microsoft.com/en-us/microsoft-365/access

rocksdb.org

Technical documentation

docs.couchbase.com

hugegraph.apache.org/docs

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

Developer

Couchbase, Inc.

Baidu

Microsoft

Facebook, Inc.

Initial release

2013

2011

2018

1992

2013

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

0.9

1902 (16.0.11328.20222), March 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2.0

commercial

Bundled with Microsoft Office

Open Source

BSD

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, C++, Go and Erlang

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux
macOS
Unix

Windows

Not a real database server, but making use of DLLs

Linux

Data scheme

schema-free

yes

schema-free

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

but not compliant to any SQL standard

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
DAO
ODBC
OLE DB

C++ API
Java API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Groovy
Java
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

asynchronous Gremlin script jobs

yes

since Access 2010 using the ACE-engine

Triggers

yes

via the TAP protocol

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

yes

ACID

but no files for transaction logging

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Users, roles and permissions

a simple user-level security was built in till version Access 2003

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.