DBMS > Google Cloud Bigtable vs. Immudb vs. Lovefield vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. Immudb vs. Lovefield vs. XTDB

Please select another system to include it in the comparison.

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.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Embeddable relational database for web apps written in pure JavaScript

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Wide column store

Key-value store

Relational DBMS

Document store

Secondary database models

Relational DBMS

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

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

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

cloud.google.com/bigtable

github.com/codenotary/immudb
immudb.io

google.github.io/lovefield

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cloud.google.com/bigtable/docs

docs.immudb.io

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

www.xtdb.com/docs

Developer

Google

Codenotary

Google

Juxt Ltd.

Initial release

2015

2020

2014

2019

Current release

1.2.3, April 2022

2.1.12, February 2017

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

MIT License

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

JavaScript

Clojure

Server operating systems

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

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

tested with Chrome, Firefox, IE, Safari

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL-like syntax

SQL-like query language

via JavaScript builder pattern

limited SQL, making use of Apache Calcite

APIs and other access methods

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

gRPC protocol
PostgreSQL wire protocol

HTTP REST
JDBC

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
Python

JavaScript

Clojure
Java

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes, each node contains all data

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)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

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

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

Codenotary brings its immutable database to the cloud
21 June 2023, TechCrunch

Immudb: Open-source database, built on a zero trust model
17 December 2021, Help Net Security

immudb (immutable database) 'tamper-proof' database - Open Source Insider
14 December 2021, ComputerWeekly.com

Storage news ticker – November 15 – Blocks and Files
15 November 2021, Blocks and Files

Codenotary introduces Software Bill of Materials service for Kubernetes
28 June 2022, ZDNet

provided by Google News

Kagiso interactive shares: all eyes on android at google I/O
11 May 2015, WhaTech

provided by Google News

Share this page