DBMS > Apache Druid vs. IBM Db2 Event Store vs. Oracle vs. SAP SQL Anywhere vs. TerminusDB

System Properties Comparison Apache Druid vs. IBM Db2 Event Store vs. Oracle vs. SAP SQL Anywhere vs. TerminusDB

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

Distributed Event Store optimized for Internet of Things use cases

Widely used RDBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS
Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
RDF store

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

druid.apache.org

www.ibm.com/products/db2-event-store

www.oracle.com/database

www.sap.com/products/technology-platform/sql-anywhere.html

terminusdb.com

Technical documentation

druid.apache.org/docs/latest/design

www.ibm.com/docs/en/db2-event-store

docs.oracle.com/en/database

help.sap.com/docs/SAP_SQL_Anywhere

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation and contributors

IBM

Oracle

SAP

formerly Sybase

DataChemist Ltd.

Initial release

2012

2017

1980

1992

2018

Current release

29.0.1, April 2024

2.0

23c, September 2023

17, July 2015

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free developer edition available

commercial

restricted free version is available

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C and C++

Prolog, Rust

Server operating systems

Linux
OS X
Unix

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

Schemaless in JSON and XML columns

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

through the embedded Spark runtime

yes

with proprietary extensions

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
HTTP API
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

yes, in C/C++, Java, .Net or Perl

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Sharding, horizontal partitioning

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Active-active shard replication

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

in-memory journaling

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

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

Role-based access control

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