DBMS > GBase vs. Google Cloud Spanner vs. HEAVY.AI vs. Lovefield

System Properties Comparison GBase vs. Google Cloud Spanner vs. HEAVY.AI vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Website

www.gbase.cn

cloud.google.com/spanner

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

Technical documentation

cloud.google.com/spanner/docs

docs.heavy.ai

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

Developer

General Data Technology Co., Ltd.

Google

HEAVY.AI, Inc.

Google

Initial release

2004

2017

2016

2014

Current release

GBase 8a, GBase 8s, GBase 8c

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 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, Java, Python

C++ and CUDA

JavaScript

Server operating systems

Linux

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

Data scheme

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

Standard with numerous extensions

yes

Query statements complying to ANSI 2011

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

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

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

yes

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

fine grained access rights according to SQL-standard

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