DBMS > Apache Impala vs. HugeGraph vs. SAP HANA vs. SAP SQL Anywhere

System Properties Comparison Apache Impala vs. HugeGraph vs. SAP HANA vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A fast-speed and highly-scalable Graph DBMS

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

impala.apache.org

github.com/hugegraph
hugegraph.apache.org

www.sap.com/products/hana.html

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

Technical documentation

impala.apache.org/impala-docs.html

hugegraph.apache.org/docs

help.sap.com/hana

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Baidu

SAP

formerly Sybase

Initial release

2013

2018

2010

1992

Current release

4.1.0, June 2022

0.9

2.0 SPS07 (April 4, 2023), April 2023

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

Linux

Linux
macOS
Unix

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris
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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Groovy
Java
Python

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

asynchronous Gremlin script jobs

SQLScript, R

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

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

Users, roles and permissions

yes

fine grained access rights according to SQL-standard

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