DBMS > Alibaba Cloud AnalyticDB for MySQL vs. BigchainDB vs. RocksDB vs. SAP Advantage Database Server vs. Solr

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. BigchainDB vs. RocksDB vs. SAP Advantage Database Server vs. Solr

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Secondary database models

Document store

Spatial DBMS

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

Score	0.76
Rank	#194	Overall
	#98	Relational DBMS

Score	0.75
Rank	#199	Overall
	#30	Document stores

Score	3.10
Rank	#92	Overall
	#15	Key-value stores

Score	3.74
Rank	#83	Overall
	#45	Relational DBMS

Score	50.60
Rank	#21	Overall
	#3	Search engines

Website

www.alibabacloud.com/product/analyticdb-for-mysql

www.bigchaindb.com

rocksdb.org

www.sap.com/products/advantage-database-server.html

lucene.apache.org/solr

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

bigchaindb.readthedocs.io/en/latest

github.com/facebook/rocksdb/wiki

lucene.apache.org/solr/resources.html

Developer

Alibaba

Facebook, Inc.

Sybase, SAP

Apache Software Foundation

Initial release

2016

2013

1993

2006

Current release

6.15.5 , February 2021

8.8.1, February 2021

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

BSD

commercial

Open Source

Apache Version 2

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

Python

C++

Java

Server operating systems

hosted

Linux

Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

C++ API
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

Supported programming languages

C#
Java
PHP
Python

Go
Haskell
Java
JavaScript
Python
Ruby

C++
Java

Delphi
Perl
PHP

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

caching of (temporary) tables can be configured

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
» more

Competitive advantages

The world leading result in TPC-DS benchmark . Paper published in VLDB 2019: AnalyticDB:...
» more

Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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