DBMS > Blueflood vs. BoltDB vs. Ehcache vs. Google BigQuery

System Properties Comparison Blueflood vs. BoltDB vs. Ehcache vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

An embedded key-value store for Go.

A widely adopted Java cache with tiered storage options

Large scale data warehouse service with append-only tables

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Website

blueflood.io

github.com/boltdb/bolt

www.ehcache.org

cloud.google.com/bigquery

Technical documentation

github.com/rax-maas/blueflood/wiki

www.ehcache.org/documentation

cloud.google.com/bigquery/docs

Developer

Rackspace

Terracotta Inc, owned by Software AG

Google

Initial release

2013

2009

2010

Current release

3.10.0, March 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Apache Version 2; commercial licenses available

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

Java

Server operating systems

Linux
OS X

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted

Data scheme

predefined 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.

Secondary indexes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

JCache

RESTful HTTP/JSON API

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

yes

by using Terracotta Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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