DBMS > Altibase vs. Google Cloud Spanner vs. Microsoft Azure Cosmos DB vs. Qdrant

System Properties Comparison Altibase vs. Google Cloud Spanner vs. Microsoft Azure Cosmos DB vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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.

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

altibase.com

cloud.google.com/spanner

azure.microsoft.com/services/cosmos-db

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

cloud.google.com/spanner/docs

learn.microsoft.com/azure/cosmos-db

qdrant.tech/documentation

Developer

Altibase

Google

Microsoft

Qdrant

Initial release

1999

2017

2014

2021

Current release

v7.3, 2023, August 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

Apache Version 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

C++

Rust

Server operating systems

AIX
HP-UX
Linux

hosted

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

Numbers, Strings, Geo, Boolean

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

ANSI SQL-92

yes

Query statements complying to ANSI 2011

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

gRPC (using protocol buffers) API
JDBC

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C
C++
Java

Go
Java
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Server-side scripts

Stored procedures

stored procedures and stored functions

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

yes

Implicit feature of the cloud service

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

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

Transaction concepts

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

ACID

Strict serializable isolation

Multi-item ACID transactions with snapshot isolation within a partition

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

fine grained access rights according to SQL-standard

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

Access rights can be defined down to the item level

Key-based authentication

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