DBMS > Amazon Aurora vs. Apache Druid vs. Manticore Search vs. SAP HANA vs. TerminusDB

System Properties Comparison Amazon Aurora vs. Apache Druid vs. Manticore Search vs. SAP HANA vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Search engine

Relational DBMS

Graph DBMS

Secondary database models

Document store

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
RDF store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

aws.amazon.com/rds/aurora

druid.apache.org

manticoresearch.com

www.sap.com/products/hana.html

terminusdb.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

druid.apache.org/docs/latest/design

manual.manticoresearch.com

help.sap.com/hana

terminusdb.github.io/terminusdb/#

Developer

Amazon

Apache Software Foundation and contributors

Manticore Software

SAP

DataChemist Ltd.

Initial release

2015

2012

2017

2010

2018

Current release

29.0.1, April 2024

6.0, February 2023

2.0 SPS07 (April 4, 2023), April 2023

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

GPL version 2

commercial

Open Source

GPL V3

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

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Implementation language

Java

C++

Prolog, Rust

Server operating systems

hosted

Linux
OS X
Unix

FreeBSD
Linux
macOS
Windows

Appliance or cloud-service

Linux

Data scheme

yes

schema-less columns are supported

Fixed schema

yes

Typing

predefined data types such as float or date

yes

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

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

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL for querying

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP/JSON API

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

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

manual/auto, time-based

Sharding

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

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, via HDFS, S3 or other storage engines

Synchronous replication based on Galera library

yes

Journaling Streams

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

ACID

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

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

Role-based access control

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