DBMS > BoltDB vs. Elasticsearch vs. Hawkular Metrics vs. SAP HANA vs. Teradata Aster

System Properties Comparison BoltDB vs. Elasticsearch vs. Hawkular Metrics vs. SAP HANA vs. Teradata Aster

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

An embedded key-value store for Go.

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

github.com/boltdb/bolt

www.elastic.co/elasticsearch

www.hawkular.org

www.sap.com/products/hana.html

Technical documentation

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

www.hawkular.org/hawkular-metrics/docs/user-guide

help.sap.com/hana

Developer

Elastic

Community supported by Red Hat

SAP

Teradata

Initial release

2013

2010

2014

2010

2005

Current release

8.6, January 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Elastic License

Open Source

Apache 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

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
OS X
Windows

Appliance or cloud-service

Linux

Data scheme

schema-free

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

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

HTTP REST

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

Go
Java
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

SQLScript, R

R packages

Triggers

yes

by using the 'percolation' feature

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

based on Cassandra

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

ES-Hadoop Connector

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

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.

Memcached and Redis integration

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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