DBMS > Manticore Search vs. Quasardb vs. SAP HANA vs. TimesTen

System Properties Comparison Manticore Search vs. Quasardb vs. SAP HANA vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Multi-storage database for search, including full-text search.

Distributed, high-performance timeseries database

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

In-Memory RDBMS compatible to Oracle

Primary database model

Search engine

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

manticoresearch.com

quasar.ai

www.sap.com/products/hana.html

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

Technical documentation

manual.manticoresearch.com

doc.quasar.ai/master

help.sap.com/hana

docs.oracle.com/database/timesten-18.1

Developer

Manticore Software

quasardb

SAP

Oracle, TimesTen Performance Software, HP

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

Initial release

2017

2009

2010

1998

Current release

6.0, February 2023

3.14.1, January 2024

2.0 SPS07 (April 4, 2023), April 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

Cloud-based only

Only available as a cloud service

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

FreeBSD
Linux
macOS
Windows

BSD
Linux
OS X
Windows

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

integer and binary

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

HTTP API

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

consistent hashing

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Source-replica replication with selectable replication factor

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

by using LevelDB

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

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

yes

fine grained access rights according to SQL-standard

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