DBMS > Adabas vs. Apache Impala vs. Splice Machine vs. XTDB vs. Yaacomo

System Properties Comparison Adabas vs. Apache Impala vs. Splice Machine vs. XTDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Analytic DBMS for Hadoop

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A general purpose database with bitemporal SQL and Datalog and graph queries

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Document store

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

impala.apache.org

splicemachine.com

github.com/xtdb/xtdb
www.xtdb.com

yaacomo.com

Technical documentation

impala.apache.org/impala-docs.html

splicemachine.com/how-it-works

www.xtdb.com/docs

Developer

Software AG

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Splice Machine

Juxt Ltd.

Q2WEB GmbH

Initial release

1971

2013

2014

2019

2009

Current release

4.1.0, June 2022

3.1, March 2021

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

AGPL 3.0, commercial license available

Open Source

MIT License

commercial

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

C++

Java

Clojure

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

yes

limited SQL, making use of Apache Calcite

yes

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

HTTP REST
JDBC

JDBC
ODBC

Supported programming languages

Natural

All languages supporting JDBC/ODBC

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Clojure
Java

Server-side scripts

Stored procedures

in Natural

yes

user defined functions and integration of map-reduce

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

Multi-source replication
Source-replica replication

yes, each node contains all data

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Yes, via Full Spark Integration

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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