DBMS > HugeGraph vs. Impala vs. Memcached vs. SAP HANA

System Properties Comparison HugeGraph vs. Impala vs. Memcached vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Analytic DBMS for Hadoop

In-memory key-value store, originally intended for caching

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

Primary database model

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	0.22
Rank	#286	Overall
	#22	Graph DBMS

Score	18.03
Rank	#40	Overall
	#25	Relational DBMS

Score	24.95
Rank	#33	Overall
	#4	Key-value stores

Score	55.09
Rank	#21	Overall
	#13	Relational DBMS

Website

github.com/hugegraph

www.cloudera.com/products/open-source/apache-hadoop/impala.html

www.memcached.org

www.sap.com/products/hana.html

Technical documentation

hugegraph.github.io/hugegraph-doc

docs.cloudera.com/documentation/enterprise/latest/topics/impala.html

github.com/memcached/memcached/wiki

help.sap.com/hana

Developer

Baidu

Cloudera

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

SAP

Initial release

2018

2013

2003

2010

Current release

0.9

4.0.0, July 2021

1.6.15, March 2022

2.0 SPS05 (June 26, 2020), June 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

BSD license

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

Java

C++

Server operating systems

Linux
macOS
Unix

Linux

FreeBSD
Linux
OS X
Unix
Windows

Appliance or cloud-service

Data scheme

yes

schema-free

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.

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

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

Proprietary protocol

JDBC
ODBC

Supported programming languages

Groovy
Java
Python

All languages supporting JDBC/ODBC

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

user defined functions and integration of map-reduce

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

selectable replication factor

none

Repcached, a Memcached patch, provides this functionallity

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

query execution via MapReduce

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

Users, roles and permissions

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

using SASL (Simple Authentication and Security Layer) protocol

yes

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