DBMS > IBM Db2 Event Store vs. Microsoft SQL Server vs. Qdrant vs. Teradata Aster

System Properties Comparison IBM Db2 Event Store vs. Microsoft SQL Server vs. Qdrant vs. Teradata Aster

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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.

Description

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Vector DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.28
Rank	#167	Overall
	#7	Vector DBMS

Website

www.ibm.com/products/db2-event-store

www.microsoft.com/en-us/sql-server

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

www.ibm.com/docs/en/db2-event-store

learn.microsoft.com/en-US/sql/sql-server

qdrant.tech/documentation

Developer

IBM

Microsoft

Qdrant

Teradata

Initial release

2017

1989

2021

2005

Current release

2.0

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C++

Rust

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

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

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

through the embedded Spark runtime

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes, but depending on the SQL-Server Edition

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.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Key-based authentication

fine grained access rights according to SQL-standard

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