DBMS > Google Cloud Spanner vs. MarkLogic vs. Sadas Engine vs. SAP HANA vs. Teradata Aster

System Properties Comparison Google Cloud Spanner vs. MarkLogic vs. Sadas Engine vs. SAP HANA vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Operational and transactional Enterprise NoSQL database

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

cloud.google.com/spanner

www.marklogic.com

www.sadasengine.com

www.sap.com/products/hana.html

Technical documentation

cloud.google.com/spanner/docs

docs.marklogic.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

help.sap.com/hana

Developer

Google

MarkLogic Corp.

SADAS s.r.l.

SAP

Teradata

Initial release

2017

2001

2006

2010

2005

Current release

11.0, December 2022

8.0

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free trial version 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

Linux
OS X
Windows

AIX
Linux
Windows

Appliance or cloud-service

Linux

Data scheme

yes

schema-free

Schema can be enforced

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

SQL92

yes

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

SQLScript, R

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

yes

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

yes

SQL Map-Reduce Framework

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

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

can act as a resource manager in an XA/JTA transaction

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, with Range Indexes

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Role-based access control at the document and subdocument levels

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

yes

fine grained access rights according to SQL-standard

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