DBMS > Hive vs. KeyDB vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. SQream DB

System Properties Comparison Hive vs. KeyDB vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Microsofts flagship relational DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

hive.apache.org

github.com/Snapchat/KeyDB
keydb.dev

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

www.sap.com/products/technology-platform/sql-anywhere.html

sqream.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

docs.keydb.dev

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

help.sap.com/docs/SAP_SQL_Anywhere

docs.sqream.com

Developer

Apache Software Foundation

initially developed by Facebook

EQ Alpha Technology Ltd.

Microsoft

SAP

formerly Sybase

SQream Technologies

Initial release

2012

2019

1989

1992

2017

Current release

3.1.3, April 2022

SQL Server 2022, November 2022

17, July 2015

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD-3

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

All OS with a Java VM

Linux

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

yes, ANSI Standard SQL Types

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

by using the Redis Search module

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Thrift

Proprietary protocol

RESP - REdis Serialization Protoco

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

ADO.NET
HTTP API
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Lua

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

yes, in C/C++, Java, .Net or Perl

user defined functions in Python

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

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

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

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

fine grained access rights according to SQL-standard

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