DBMS > Apache Druid vs. Heroic vs. RocksDB vs. SAP Advantage Database Server vs. Snowflake

System Properties Comparison Apache Druid vs. Heroic vs. RocksDB vs. SAP Advantage Database Server vs. Snowflake

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

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

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Key-value store

Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

druid.apache.org

github.com/spotify/heroic

rocksdb.org

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

www.snowflake.com

Technical documentation

druid.apache.org/docs/latest/design

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Spotify

Facebook, Inc.

Sybase, SAP

Snowflake Computing Inc.

Initial release

2012

2014

2013

1993

2014

Current release

29.0.1, April 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

BSD

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++

Server operating systems

Linux
OS X
Unix

Linux

Linux
Windows

hosted

Data scheme

yes

schema-less columns are supported

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

C++ API
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Delphi
Perl
PHP

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

yes

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

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.

yes

caching of (temporary) tables can be configured

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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