DBMS > AnzoGraph DB vs. Apache Impala vs. H2 vs. Teradata Aster

System Properties Comparison AnzoGraph DB vs. Apache Impala vs. H2 vs. Teradata Aster

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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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Analytic DBMS for Hadoop

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Platform for big data analytics on multistructured data sources and types

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Website

cambridgesemantics.com/anzograph

impala.apache.org

www.h2database.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

impala.apache.org/impala-docs.html

www.h2database.com/html/main.html

Developer

Cambridge Semantics

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Thomas Mueller

Teradata

Initial release

2018

2013

2005

Current release

2.3, January 2021

4.1.0, June 2022

2.2.220, July 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

All OS with a Java VM

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

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

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like DML and DDL statements

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C++
Java
Python

All languages supporting JDBC/ODBC

Java

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

user defined functions and integration of map-reduce

Java Stored Procedures and User-Defined Functions

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Kerberos/HDFS data loading

yes

query execution via MapReduce

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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 and roles

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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More resources

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
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