DBMS > Apache Impala vs. Graph Engine vs. Microsoft SQL Server vs. SAP Adaptive Server vs. TerarkDB

System Properties Comparison Apache Impala vs. Graph Engine vs. Microsoft SQL Server vs. SAP Adaptive Server vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Microsofts flagship relational DBMS

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

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

Graph DBMS
Key-value store

Relational DBMS

Key-value store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

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

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

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

Website

impala.apache.org

www.graphengine.io

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

www.sap.com/products/technology-platform/sybase-ase.html

github.com/bytedance/terarkdb

Technical documentation

impala.apache.org/impala-docs.html

www.graphengine.io/docs/manual

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

help.sap.com/docs/SAP_ASE

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

SAP, Sybase

ByteDance, originally Terark

Initial release

2013

2010

1989

1987

2016

Current release

4.1.0, June 2022

SQL Server 2022, November 2022

16.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

commercial

restricted free version is available

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

.NET and C

C++

C and C++

C++

Server operating systems

Linux

.NET

Linux
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

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

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

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

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

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

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

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

horizontal partitioning

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

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

yes

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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