DBMS > Apache Pinot vs. Graph Engine vs. HEAVY.AI vs. Kdb vs. Microsoft SQL Server

System Properties Comparison Apache Pinot vs. Graph Engine vs. HEAVY.AI vs. Kdb vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

High performance Time Series DBMS

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

pinot.apache.org

www.graphengine.io

github.com/heavyai/heavydb
www.heavy.ai

kx.com

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

Technical documentation

docs.pinot.apache.org

www.graphengine.io/docs/manual

docs.heavy.ai

code.kx.com

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

Developer

Apache Software Foundation and contributors

Microsoft

HEAVY.AI, Inc.

Kx Systems, a division of First Derivatives plc

Microsoft

Initial release

2015

2010

2016

2000

kdb was released 2000, kdb+ in 2003

1989

Current release

1.0.0, September 2023

5.10, January 2022

3.6, May 2018

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

Apache Version 2; enterprise edition available

commercial

free 32-bit version

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

.NET and C

C++ and CUDA

C++

Server operating systems

All OS with a Java JDK11 or higher

.NET

Linux

Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

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

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (q)

yes

APIs and other access methods

JDBC

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

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

Supported programming languages

Go
Java
Python

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

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

Server-side scripts

Stored procedures

yes

user defined functions

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

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Round robin

horizontal partitioning

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent 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

rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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