DBMS > BoltDB vs. Couchbase vs. HugeGraph vs. Manticore Search vs. RocksDB

System Properties Comparison BoltDB vs. Couchbase vs. HugeGraph vs. Manticore Search 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

Multi-storage database for search, including full-text search.

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

Time Series DBMS

using the Manticore Columnar Library

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	0.22
Rank	#312	Overall
	#21	Search engines

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

Website

github.com/boltdb/bolt

www.couchbase.com

github.com/hugegraph
hugegraph.apache.org

manticoresearch.com

rocksdb.org

Technical documentation

docs.couchbase.com

hugegraph.apache.org/docs

manual.manticoresearch.com

github.com/facebook/rocksdb/wiki

Developer

Couchbase, Inc.

Baidu

Manticore Software

Facebook, Inc.

Initial release

2013

2011

2018

2017

2013

Current release

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

0.9

6.0, February 2023

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

Open Source

GPL version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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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

FreeBSD
Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

also supports composite index and range index

yes

full-text index on all search fields

SQL

Support of SQL

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

SQL-like query language

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

C++ API
Java API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Groovy
Java
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

user defined functions

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

yes

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

Sharding

Partitioning is done manually, search queries against distributed index is supported

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

Synchronous replication based on Galera library

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

Transaction concepts

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

yes

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

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