DBMS > Apache Pinot vs. CrateDB vs. Oracle vs. SAP Advantage Database Server vs. Sphinx

System Properties Comparison Apache Pinot vs. CrateDB vs. Oracle vs. SAP Advantage Database Server vs. Sphinx

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

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Distributed Database based on Lucene

Widely used RDBMS

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Search engine

Secondary database models

Relational DBMS

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

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

pinot.apache.org

cratedb.com

www.oracle.com/database

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

sphinxsearch.com

Technical documentation

docs.pinot.apache.org

cratedb.com/docs

docs.oracle.com/en/database

sphinxsearch.com/docs

Developer

Apache Software Foundation and contributors

Crate

Oracle

Sybase, SAP

Sphinx Technologies Inc.

Initial release

2015

2013

1980

1993

2001

Current release

1.0.0, September 2023

5.8.1, August 2024

23c, September 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

restricted free version is available

commercial

Open Source

GPL version 2, commercial licence available

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++

C++

Server operating systems

All OS with a Java JDK11 or higher

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

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

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

with proprietary extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol

Supported programming languages

Go
Java
Python

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

Delphi
Perl
PHP

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions (Javascript)

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Sharding, horizontal partitioning

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication
Source-replica replication

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

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

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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'

caching of (temporary) tables can be configured

User concepts

Access control

rights management via user accounts

fine grained access rights according to SQL-standard

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