DBMS > Apache Impala vs. Microsoft SQL Server vs. Oracle Rdb vs. PlanetScale vs. TerarkDB

System Properties Comparison Apache Impala vs. Microsoft SQL Server vs. Oracle Rdb vs. PlanetScale vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Microsofts flagship relational DBMS

Scalable, distributed, serverless MySQL database platform built on top of Vitess

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

impala.apache.org

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

www.oracle.com/database/technologies/related/rdb.html

planetscale.com

github.com/bytedance/terarkdb

Technical documentation

impala.apache.org/impala-docs.html

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

www.oracle.com/database/technologies/related/rdb-doc.html

planetscale.com/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

PlanetScale

ByteDance, originally Terark

Initial release

2013

1989

1984

2020

2016

Current release

4.1.0, June 2022

SQL Server 2022, November 2022

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted free version is available

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Server operating systems

Linux

Linux
Windows

HP Open VMS

Docker
Linux
macOS

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
MySQL protocol
ODBC

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

yes

proprietary syntax

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes, on a single node

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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