DBMS > Google Cloud Spanner vs. Qdrant vs. Teradata Aster vs. Trafodion

System Properties Comparison Google Cloud Spanner vs. Qdrant vs. Teradata Aster vs. Trafodion

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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.

Apache Trafodion has been retired in 2021. Therefore it is excluded 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.

A high-performance vector database with neural network or semantic-based matching

Platform for big data analytics on multistructured data sources and types

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Vector DBMS

Relational DBMS

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

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

cloud.google.com/spanner

github.com/qdrant/qdrant
qdrant.tech

trafodion.apache.org

Technical documentation

cloud.google.com/spanner/docs

qdrant.tech/documentation

trafodion.apache.org/documentation.html

Developer

Google

Qdrant

Teradata

Apache Software Foundation, originally developed by HP

Initial release

2017

2021

2005

2014

Current release

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

C++, Java

Server operating systems

hosted

Docker
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

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

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

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, 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

in Aster File Store

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C
C#
C++
Java
Python
R

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

R packages

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

Collection-level replication

yes

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

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

SQL Map-Reduce Framework

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

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

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

Key-based authentication

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Google Cloud Spanner gets dual-region configuration option
23 July 2024, InfoWorld

Google Cloud adds graph and vector search features to Spanner database
2 August 2024, Techzine Europe

Google Cloud Enhances Spanner with Dual-Region Configuration
1 August 2024, InfoQ.com

New features make Google's Spanner a database for AI
1 August 2024, TechTarget

Google Cloud expands its database portfolio with new AI capabilities
1 August 2024, TechCrunch

provided by Google News

Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

provided by Google News

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Teradata Integrates Big Data Analytic Architecture
22 October 2012, PR Newswire

An American Dream Story, With A Silicon Valley Twist
14 August 2013, Forbes

Gartner, IBM, Teradata make Big Data announcements
17 October 2012, ZDNet

provided by Google News

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