DBMS > BoltDB vs. Couchbase vs. Google Cloud Spanner vs. Heroic vs. Memcached

System Properties Comparison BoltDB vs. Couchbase vs. Google Cloud Spanner vs. Heroic vs. Memcached

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 horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

In-memory key-value store, originally intended for caching

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	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Website

github.com/boltdb/bolt

www.couchbase.com

cloud.google.com/spanner

github.com/spotify/heroic

www.memcached.org

Technical documentation

docs.couchbase.com

cloud.google.com/spanner/docs

spotify.github.io/heroic

github.com/memcached/memcached/wiki

Developer

Couchbase, Inc.

Google

Spotify

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Initial release

2013

2011

2017

2014

2003

Current release

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

1.6.25, March 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

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

commercial

Open Source

Apache 2.0

Open Source

BSD license

Cloud-based only

Only available as a cloud service

yes

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Unix
Windows

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

via Elasticsearch

SQL

Support of SQL

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

yes

Query statements complying to ANSI 2011

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Proprietary protocol

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

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

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication with 3 replicas for regional instances.

yes

none

Repcached, a Memcached patch, provides this functionallity

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

yes

ACID

Strict serializable isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Ephemeral buckets

User concepts

Access control

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

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

yes

using SASL (Simple Authentication and Security Layer) protocol

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