DBMS > HugeGraph vs. LevelDB vs. Sadas Engine vs. Teradata Aster

System Properties Comparison HugeGraph vs. LevelDB vs. Sadas Engine vs. Teradata Aster

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

A fast-speed and highly-scalable Graph DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Platform for big data analytics on multistructured data sources and types

Primary database model

Graph DBMS

Key-value store

Relational DBMS

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

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

github.com/google/leveldb

www.sadasengine.com

Technical documentation

hugegraph.apache.org/docs

github.com/google/leveldb/blob/main/doc/index.md

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Baidu

Google

SADAS s.r.l.

Teradata

Initial release

2018

2011

2006

2005

Current release

0.9

1.23, February 2021

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud 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

Illumos
Linux
OS X
Windows

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

yes

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Groovy
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

R packages

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

Users, roles and permissions

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

全面升级！Apache HugeGraph 1.2.0版本发布_apach hugegraph
27 February 2024, CSDN

HugeGraph 部署和Hubble1.0.0的数据导入Bug修复_hugegraph-hubble导入数据时选择属性显示不全
18 October 2023, CSDN

provided by Google News

LevelDB in Ruby — SitePoint
22 October 2014, SitePoint

Microsoft Teams stores auth tokens as cleartext in Windows, Linux, Macs
14 September 2022, BleepingComputer

Pliops unveils XDP-Rocks for RocksDB – Blocks and Files
19 October 2022, Blocks & Files

XanMod, Liquorix Kernels Offer Some Advantages On AMD Ryzen 5 Notebook
26 July 2021, Phoronix

Rust-Based Info Stealers Abuse GitHub Codespaces
19 May 2023, Trend Micro

provided by Google News

Mellanox InfiniBand Helps Accelerate Teradata Aster Big Analytics Appliance
23 April 2024, Yahoo Movies UK

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

Discover Value in Big Data with Free Aster Express
17 October 2012, PR Newswire

provided by Google News

Share this page