DBMS > Apache Druid vs. Coveo vs. Derby vs. RocksDB vs. SAP Adaptive Server

System Properties Comparison Apache Druid vs. Coveo vs. Derby vs. RocksDB vs. SAP Adaptive Server

Editorial information provided by DB-Engines

Name

Description

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

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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	2.11
Rank	#118	Overall
	#11	Search engines

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

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

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

druid.apache.org/docs/latest/design

docs.coveo.com

db.apache.org/derby/manuals/index.html

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_ASE

Developer

Apache Software Foundation and contributors

Coveo

Apache Software Foundation

Facebook, Inc.

SAP, Sybase

Initial release

2012

1997

2013

1987

Current release

29.0.1, April 2024

10.17.1.0, November 2023

9.2.1, May 2024

16.0

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache version 2

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++

C and C++

Server operating systems

Linux
OS X
Unix

hosted

All OS with a Java VM

Linux

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

yes

schema-less columns are supported

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

yes

schema-free

yes

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

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

JDBC

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
Java
JavaScript
Python

Java

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Source-replica replication

yes

Multi-source replication
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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

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

User concepts

Access control

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

granular access controls, API key management, content filters

fine grained access rights according to SQL-standard

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