DBMS > Axibase vs. Elasticsearch vs. Riak KV vs. SurrealDB vs. Teradata Aster

System Properties Comparison Axibase vs. Elasticsearch vs. Riak KV vs. SurrealDB 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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

Distributed, fault tolerant key-value store

A fully ACID transactional, developer-friendly, multi-model DBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

Time Series DBMS

Search engine

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Document store
Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

axibase.com/docs/atsd/finance

www.elastic.co/elasticsearch

surrealdb.com

Technical documentation

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

www.tiot.jp/riak-docs/riak/kv/latest

surrealdb.com/docs

Developer

Axibase Corporation

Elastic

OpenSource, formerly Basho Technologies

SurrealDB Ltd

Teradata

Initial release

2013

2010

2009

2022

2005

Current release

15585

8.6, January 2023

3.2.0, December 2022

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Elastic License

Open Source

Apache version 2, commercial enterprise edition

Open Source

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

Erlang

Rust

Server operating systems

Linux

All OS with a Java VM

Linux
OS X

Linux
macOS
Windows

Linux

Data scheme

yes

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

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java API
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

GraphQL
RESTful HTTP API
WebSocket

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Deno
Go
JavaScript (Node.js)
Rust

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Erlang

R packages

Triggers

yes

by using the 'percolation' feature

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

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

yes

ES-Hadoop Connector

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

links between data sets can be stored

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.

Memcached and Redis integration

User concepts

Access control

yes, using Riak Security

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

More information provided by the system vendor

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