DBMS > Badger vs. Derby vs. Firebolt vs. Google Cloud Bigtable

System Properties Comparison Badger vs. Derby vs. Firebolt vs. Google Cloud Bigtable

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

Primary database model

Key-value store

Relational DBMS

Key-value store
Wide column store

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Website

github.com/dgraph-io/badger

db.apache.org/derby

www.firebolt.io

cloud.google.com/bigtable

Technical documentation

godoc.org/github.com/dgraph-io/badger

db.apache.org/derby/manuals/index.html

docs.firebolt.io

cloud.google.com/bigtable/docs

Developer

DGraph Labs

Apache Software Foundation

Firebolt Analytics Inc.

Google

Initial release

2017

1997

2020

2015

Current release

10.17.1.0, November 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

commercial

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

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC

.Net
ODBC
RESTful HTTP API

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

Supported programming languages

Java

Go
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

depending on storage layer

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

JDBC tutorial: Easy installation and setup with Apache Derby
20 December 2019, TheServerSide.com

Installing Apache Hive 3.1.2 on Windows 10 | by Hadi Fadlallah
3 May 2020, Towards Data Science

The Arrival of Java 20
21 March 2023, blogs.oracle.com

The Ultimate Open Source Database List Profiling 16 Software Tools
30 May 2019, Solutions Review

The Apache® Software Foundation Announces 18 Years of Open Source Leadership
28 March 2017, GlobeNewswire

provided by Google News

10 Best Data Pipeline Tools of 2024 to Boost Your Productivity
20 February 2024, Datamation

Cloud data unicorn Firebolt fires dozens of employees
7 September 2022, CTech

Firebolt, a data warehouse startup, raises $100M at a $1.4B valuation for faster, cheaper analytics on large data sets
26 January 2022, TechCrunch

Firebolt vs Snowflake | Data Warehousing Platform Comparison
1 April 2022, TechRepublic

Firebolt, Israeli Cloud Data Warehouse Startup Forklifts Forward
5 January 2021, Forbes

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

Share this page