DBMS > BoltDB vs. Google Cloud Bigtable vs. IBM Cloudant vs. Manticore Search vs. Snowflake

System Properties Comparison BoltDB vs. Google Cloud Bigtable vs. IBM Cloudant vs. Manticore Search vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Database as a Service offering based on Apache CouchDB

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Key-value store

Key-value store
Wide column store

Document store

Search engine

Relational DBMS

Secondary database models

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	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

github.com/boltdb/bolt

cloud.google.com/bigtable

www.ibm.com/products/cloudant

manticoresearch.com

www.snowflake.com

Technical documentation

cloud.google.com/bigtable/docs

cloud.ibm.com/docs/Cloudant

manual.manticoresearch.com

docs.snowflake.net/manuals/index.html

Developer

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Manticore Software

Snowflake Computing Inc.

Initial release

2013

2015

2010

2017

2014

Current release

6.0, February 2023

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
macOS
Windows

hosted

Data scheme

schema-free

Fixed schema

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP/JSON API

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

CLI Client
JDBC
ODBC

Supported programming languages

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Atomic single-row operations

atomic operations within a document possible

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users can be defined per database

Users with fine-grained authorization concept, user roles and pluggable authentication

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