DBMS > ClickHouse vs. Interbase vs. Microsoft Access vs. SQream DB vs. Titan

System Properties Comparison ClickHouse vs. Interbase vs. Microsoft Access vs. SQream DB vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Light-weight proven RDBMS

originally from Borland

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

a GPU-based, columnar RDBMS for big data analytics workloads

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

clickhouse.com

www.embarcadero.com/products/interbase

www.microsoft.com/en-us/microsoft-365/access

sqream.com

github.com/thinkaurelius/titan

Technical documentation

clickhouse.com/docs

docs.embarcadero.com/products/interbase

developer.microsoft.com/en-us/access

docs.sqream.com

github.com/thinkaurelius/titan/wiki

Developer

Clickhouse Inc.

Embarcadero

Microsoft

SQream Technologies

Aurelius, owned by DataStax

Initial release

2016

1984

1992

2017

2012

Current release

v24.4.1.2088-stable, May 2024

InterBase 2020, December 2019

1902 (16.0.11328.20222), March 2019

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

commercial

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C++

C++, CUDA, Haskell, Java, Scala

Java

Server operating systems

FreeBSD
Linux
macOS

Android
iOS
Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Close to ANSI SQL (SQL/JSON + extensions)

yes

but not compliant to any SQL standard

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
JDBC
ODBC

ADO.NET
DAO
ODBC
OLE DB

.Net
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C++
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

yes

since Access 2010 using the ACE-engine

user defined functions in Python

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

horizontal and vertical partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Interbase Change Views

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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 rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

User authentification and security via Rexster Graph Server

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