DBMS > etcd vs. Firebird vs. Google BigQuery vs. VictoriaMetrics

System Properties Comparison etcd vs. Firebird vs. Google BigQuery vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Firebird is an open source RDBMS forked from Borland's InterBase

Large scale data warehouse service with append-only tables

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.firebirdsql.org

cloud.google.com/bigquery

victoriametrics.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigquery/docs

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Firebird Foundation

Google

VictoriaMetrics

Initial release

2000

As fork of Borland's InterBase

2010

2018

Current release

3.4, August 2019

5.0.0, January 2024

v1.91, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Initial Developer's Public License

commercial

Open Source

Apache Version 2.0

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 and C++

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

FreeBSD
Linux
macOS
OpenBSD

Data 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

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
JSON over HTTP

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP/JSON API

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

PSQL

user defined functions

in JavaScript

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Source-replica replication

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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.

User concepts

Access control

Users with fine-grained authorization concept

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

Google Cloud Identity & Access Management (IAM)

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