DBMS > Amazon CloudSearch vs. HarperDB vs. Heroic vs. XTDB vs. Yaacomo

System Properties Comparison Amazon CloudSearch vs. HarperDB vs. Heroic vs. XTDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A general purpose database with bitemporal SQL and Datalog and graph queries

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

aws.amazon.com/cloudsearch

www.harperdb.io

github.com/spotify/heroic

github.com/xtdb/xtdb
www.xtdb.com

yaacomo.com

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.harperdb.io/docs

spotify.github.io/heroic

www.xtdb.com/docs

Developer

Amazon

HarperDB

Spotify

Juxt Ltd.

Q2WEB GmbH

Initial release

2012

2017

2014

2019

2009

Current release

3.1, August 2021

1.19, September 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Node.js

Java

Clojure

Server operating systems

hosted

Linux
OS X

All OS with a Java 8 (and higher) VM
Linux

Android
Linux
Windows

Data scheme

yes

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes

yes, extensible-data-notation format

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.

Secondary indexes

yes

all search fields are automatically indexed

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like data manipulation statements

limited SQL, making use of Apache Calcite

yes

APIs and other access methods

HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP REST
JDBC

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Clojure
Java

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

A table resides as a whole on one (or more) nodes in a cluster

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

the nodes on which a table resides can be defined

yes

yes, each node contains all data

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

authentication via encrypted signatures

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

DB-Engines blog posts

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

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