DBMS > Databend vs. Google Cloud Bigtable vs. Lovefield vs. RocksDB

System Properties Comparison Databend vs. Google Cloud Bigtable vs. Lovefield vs. RocksDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Key-value store

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

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

github.com/datafuselabs/databend
www.databend.com

cloud.google.com/bigtable

google.github.io/lovefield

rocksdb.org

Technical documentation

docs.databend.com

cloud.google.com/bigtable/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

github.com/facebook/rocksdb/wiki

Developer

Databend Labs

Google

Facebook, Inc.

Initial release

2021

2015

2014

2013

Current release

1.0.59, April 2023

2.1.12, February 2017

9.4.0, June 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 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

JavaScript

C++

Server operating systems

hosted
Linux
macOS

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

yes

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

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

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

Atomic single-row operations

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

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

Apache Iceberg Rust Released
9 September 2024, iProgrammer

Â£1.1 Million in AddisonMckee Tube Bending Technologies Provides Dinex with Outstanding OEM Credentials
24 May 2007, news.thomasnet.com

provided by Google News

Google Cloud adds graph processing to Spanner, SQL support to Bigtable
1 August 2024, InfoWorld

Google introduces Bigtable SQL access and Spanner's new AI-ready features
1 August 2024, ZDNet

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

Google Cloud Adds GenAI, Core Enhancements Across Data Platform
1 August 2024, The New Stack

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

provided by Google News

AMD EPYC vs. Intel Xeon Cascadelake With Facebook's RocksDB Database
17 October 2019, Phoronix

Pliops Unveils Accelerated Key-Value Store That Boosts RocksDB Performance by 20x at OCP Global Summit
18 October 2022, GlobeNewswire

Facebook’s MyRocks Truly Rocks!
21 September 2020, Open Source For You

Meta’s Velox Means Database Performance Is Not Subject To Interpretation
31 August 2022, The Next Platform

The Journey to a Million Ops / Sec / Node in Venice
16 March 2024, InfoQ.com

provided by Google News

Share this page