DBMS > AnzoGraph DB vs. Elasticsearch vs. RocksDB vs. Teradata Aster vs. Tibero

System Properties Comparison AnzoGraph DB vs. Elasticsearch vs. RocksDB vs. Teradata Aster vs. Tibero

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Platform for big data analytics on multistructured data sources and types

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.elastic.co/elasticsearch

rocksdb.org

us.tmaxsoft.com/products/tibero

Technical documentation

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

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

github.com/facebook/rocksdb/wiki

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Cambridge Semantics

Elastic

Facebook, Inc.

Teradata

TmaxSoft

Initial release

2018

2010

2013

2005

2003

Current release

2.3, January 2021

8.6, January 2023

9.2.1, May 2024

6, April 2015

License

Commercial or Open Source

commercial

free trial version available

Open Source

Elastic License

Open Source

BSD

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++

C and Assembler

Server operating systems

Linux

All OS with a Java VM

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

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

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

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

in Aster File Store

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

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

SQL-like query language

yes

APIs and other access methods

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

Java API
RESTful HTTP/JSON API

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C++
Java
Python

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
Python
R

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

R packages

Persistent Stored Procedure (PSM)

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

Sharding

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

ES-Hadoop Connector

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

yes

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

Memcached and Redis integration

yes

planned for next version

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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