DBMS > Databend vs. GBase vs. Google Cloud Spanner vs. SAP Advantage Database Server vs. SiriDB

System Properties Comparison Databend vs. GBase vs. Google Cloud Spanner vs. SAP Advantage Database Server vs. SiriDB

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

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.

Low-cost RDBMS with access to ISAM and FoxPro data structures

Open Source Time Series DBMS

Primary database model

Relational DBMS

Time Series DBMS

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

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

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

www.gbase.cn

cloud.google.com/spanner

www.sap.com/products/advantage-database-server.html

siridb.com

Technical documentation

docs.databend.com

cloud.google.com/spanner/docs

docs.siridb.com

Developer

Databend Labs

General Data Technology Co., Ltd.

Google

Sybase, SAP

Cesbit

Initial release

2021

2004

2017

1993

2017

Current release

1.0.59, April 2023

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Rust

C, Java, Python

Server operating systems

hosted
Linux
macOS

Linux

hosted

Linux
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Go
Java
JavaScript (Node.js)
Python

Delphi
Perl
PHP

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

yes

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

yes

ACID

Strict serializable isolation

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.

caching of (temporary) tables can be configured

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

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

simple rights management via user accounts

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