DBMS > ArcadeDB vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Riak TS vs. searchxml

System Properties Comparison ArcadeDB vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Riak TS vs. searchxml

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Time Series DBMS

Relational DBMS

Time Series DBMS

Native XML DBMS
Search engine

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

arcadedb.com

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

www.searchxml.net/category/products

Technical documentation

docs.arcadedb.com

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

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

www.searchxml.net/support/handouts

Developer

Arcade Data

Spotify

Microsoft

Open Source, formerly Basho Technologies

informationpartners gmbh

Initial release

2021

2014

2016

2015

Current release

September 2021

3.0.0, September 2022

1.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

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

Java

C++

Erlang

C++

Server operating systems

All OS with a Java VM

hosted

Linux
OS X

Windows

Data scheme

schema-free

yes

schema-free

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

Secondary indexes

yes

via Elasticsearch

yes

restricted

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

yes, limited

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

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

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Java

C#
Java
PHP

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Transact SQL

Erlang

yes

on the application server

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

links between datasets can be stored

Transaction concepts

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

ACID

multiple readers, single writer

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.

User concepts

Access control

yes

Domain, group and role-based access control at the document level and for application services

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