DBMS > Apache Druid vs. HarperDB vs. Microsoft SQL Server vs. Newts vs. SAP Advantage Database Server

System Properties Comparison Apache Druid vs. HarperDB vs. Microsoft SQL Server vs. Newts vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Microsofts flagship relational DBMS

Time Series DBMS based on Cassandra

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

druid.apache.org

www.harperdb.io

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

opennms.github.io/newts

www.sap.com/products/advantage-database-server.html

Technical documentation

druid.apache.org/docs/latest/design

docs.harperdb.io/docs

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

github.com/OpenNMS/newts/wiki

Developer

Apache Software Foundation and contributors

HarperDB

Microsoft

OpenNMS Group

Sybase, SAP

Initial release

2012

2017

1989

2014

1993

Current release

29.0.1, April 2024

3.1, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community edition available

commercial

restricted free version is available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Node.js

C++

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X

Linux
Windows

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-less columns are supported

dynamic schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL

Support of SQL

SQL for querying

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

HTTP REST
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Java

Delphi
Perl
PHP

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

A table resides as a whole on one (or more) nodes in a cluster

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

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

the nodes on which a table resides can be defined

yes, but depending on the SQL-Server Edition

selectable replication factor

based on Cassandra

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

caching of (temporary) tables can be configured

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles

fine grained access rights according to SQL-standard

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