DBMS > Google Cloud Datastore vs. QuestDB vs. SAP HANA vs. Teradata

System Properties Comparison Google Cloud Datastore vs. QuestDB vs. SAP HANA vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A high performance open source SQL database for time series data

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

cloud.google.com/datastore

questdb.io

www.sap.com/products/hana.html

www.teradata.com

Technical documentation

cloud.google.com/datastore/docs

questdb.io/docs

help.sap.com/hana

docs.teradata.com

Developer

Google

QuestDB Technology Inc

SAP

Teradata

Initial release

2008

2014

2010

1984

Current release

2.0 SPS07 (April 4, 2023), April 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Java (Zero-GC), C++, Rust

Server operating systems

hosted

Linux
macOS
Windows

Appliance or cloud-service

hosted
Linux

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

yes

Typing

predefined data types such as float or date

yes, details here

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

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like query language (GQL)

SQL with time-series extensions

yes

SQL 2016 + extensions

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

using Google App Engine

SQLScript, R

yes

UDFs, stored procedures, table functions in parallel

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by timestamps)

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Source-replica replication with eventual consistency

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID for single-table writes

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

through memory mapped files

yes

User concepts

Access control

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

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

Combine Java and Rust Code Coverage in a Polyglot Project
10 September 2024

Weather data visualization and forecasting with QuestDB, Kafka and Grafana
4 September 2024

Building a new vector based storage model
22 August 2024

Calibrating VWAP executions with QuestDB and Grafana
16 August 2024

Write Time: a call for community writers
13 August 2024

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