DBMS > Google Cloud Bigtable vs. InfluxDB vs. Prometheus vs. Qdrant vs. RocksDB

System Properties Comparison Google Cloud Bigtable vs. InfluxDB vs. Prometheus vs. Qdrant vs. RocksDB

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.

DBMS for storing time series, events and metrics

Open-source Time Series DBMS and monitoring system

A high-performance vector database with neural network or semantic-based matching

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store
Wide column store

Time Series DBMS

Vector DBMS

Key-value store

Secondary database models

Spatial DBMS

with GEO package

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

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

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

cloud.google.com/bigtable

www.influxdata.com/products/influxdb-overview

prometheus.io

github.com/qdrant/qdrant
qdrant.tech

rocksdb.org

Technical documentation

cloud.google.com/bigtable/docs

docs.influxdata.com/influxdb

prometheus.io/docs

qdrant.tech/documentation

github.com/facebook/rocksdb/wiki

Developer

Google

Qdrant

Facebook, Inc.

Initial release

2015

2013

2015

2021

2013

Current release

2.7.6, April 2024

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

BSD

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

Rust

C++

Server operating systems

hosted

Linux
OS X

through Homebrew

Linux
Windows

Docker
Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

Numeric data only

Numbers, Strings, Geo, Boolean

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.

Import of XML data possible

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

HTTP API
JSON over UDP

RESTful HTTP/JSON API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

C++ API
Java API

Supported programming languages

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

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

in enterprise version only

yes

by Federation

Collection-level replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

none

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

yes

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

Depending on used storage engine

yes

User concepts

Access control

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

simple rights management via user accounts

Key-based authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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