DBMS > Google BigQuery vs. InterSystems Caché vs. OceanBase vs. SAP HANA

System Properties Comparison Google BigQuery vs. InterSystems Caché vs. OceanBase vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

A multi-model DBMS and application server

A distributed, high available RDBMS compatible with Oracle and MySQL

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

Document store
Wide column store

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.57
Rank	#149	Overall
	#69	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

cloud.google.com/bigquery

www.intersystems.com/products/cache

en.oceanbase.com

www.sap.com/products/hana.html

Technical documentation

cloud.google.com/bigquery/docs

docs.intersystems.com

en.oceanbase.com/docs/oceanbase-database

help.sap.com/hana

Developer

Google

InterSystems

OceanBase

previously Alibaba and Ant Group

SAP

Initial release

2010

1997

2010

Current release

2018.1.4, May 2020

4.3.0, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

Appliance or cloud-service

Data scheme

yes

depending on used data model

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

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using Paxos

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

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

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles

Access rights for users, groups and roles according to SQL-standard

yes

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