DBMS > Databend vs. Google BigQuery vs. Interbase vs. SAP Adaptive Server vs. TimesTen

System Properties Comparison Databend vs. Google BigQuery vs. Interbase vs. SAP Adaptive Server vs. TimesTen

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

Large scale data warehouse service with append-only tables

Light-weight proven RDBMS

originally from Borland

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	3.78
Rank	#77	Overall
	#41	Relational DBMS

Score	32.67
Rank	#25	Overall
	#17	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

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

cloud.google.com/bigquery

www.embarcadero.com/products/interbase

www.sap.com/products/technology-platform/sybase-ase.html

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.databend.com

cloud.google.com/bigquery/docs

docs.embarcadero.com/products/interbase

help.sap.com/docs/SAP_ASE

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Databend Labs

Google

Embarcadero

SAP, Sybase

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2021

2010

1984

1987

1998

Current release

1.0.59, April 2023

InterBase 2020, December 2019

16.0

Release 22.1

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

Rust

C and C++

Server operating systems

hosted
Linux
macOS

hosted

Android
iOS
Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C
C++
Cobol
Java
Java
Perl
PHP
Python

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Interbase procedure and trigger language

Java and Transact-SQL

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Interbase Change Views

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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