DBMS > Dolt vs. GBase vs. Google Cloud Bigtable vs. Kinetica vs. LeanXcale

System Properties Comparison Dolt vs. GBase vs. Google Cloud Bigtable vs. Kinetica vs. LeanXcale

Editorial information provided by DB-Engines

Name

Description

A MySQL compatible DBMS with Git-like versioning of data and schema

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Fully vectorized database across both GPUs and CPUs

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Document store

Spatial DBMS
Time Series DBMS

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

Score	0.93
Rank	#194	Overall
	#90	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

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

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Website

github.com/dolthub/dolt
www.dolthub.com

www.gbase.cn

cloud.google.com/bigtable

www.kinetica.com

www.leanxcale.com

Technical documentation

docs.dolthub.com

cloud.google.com/bigtable/docs

docs.kinetica.com

Developer

DoltHub Inc

General Data Technology Co., Ltd.

Google

Kinetica

LeanXcale

Initial release

2018

2004

2015

2012

2015

Current release

GBase 8a, GBase 8s, GBase 8c

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

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

C, Java, Python

C, C++

Server operating systems

Linux
macOS
Windows

Linux

hosted

Linux

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Standard with numerous extensions

SQL-like DML and DDL statements

yes

through Apache Derby

APIs and other access methods

CLI Client
HTTP REST

ADO.NET
C API
JDBC
ODBC

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

JDBC
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

C++
Java
JavaScript (Node.js)
Python

C
Java
Scala

Server-side scripts

Stored procedures

yes

currently in alpha release

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes

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

Source-replica replication

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)

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

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

GPU vRAM or System RAM

yes

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

yes

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

Access rights for users and roles on table level

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

Dolt- A Version Controlled Database
29 January 2024, iProgrammer

Dolt, a Relational Database with Git-Like Cloning Features
19 August 2020, The New Stack

Data Versioning at Scale: Chaos and Chaos Management
10 February 2023, InfoQ.com

Top Data Version Control Tools for Machine Learning Research in 2023
24 July 2023, MarkTechPost

25 Hot New Data Tools and What They DON’T Do
14 May 2020, Towards Data Science

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

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica: AI is a ‘killer app’ for data analytics
2 May 2023, Blocks & Files

Kinetica Taps Dell for Hardware
12 June 2018, Finovate

provided by Google News

Share this page