DBMS > Adabas vs. LevelDB vs. Milvus vs. Spark SQL vs. TimesTen

System Properties Comparison Adabas vs. LevelDB vs. Milvus vs. Spark SQL vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

used typically together with the Natural programming platform

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A DBMS designed for efficient storage of vector data and vector similarity searches

Spark SQL is a component on top of 'Spark Core' for structured data processing

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

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

github.com/google/leveldb

milvus.io

spark.apache.org/sql

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

milvus.io/docs/overview.md

spark.apache.org/docs/latest/sql-programming-guide.html

docs.oracle.com/database/timesten-18.1

Developer

Software AG

Google

Apache Software Foundation

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1971

2011

2019

2014

1998

Current release

1.23, February 2021

2.3.4, January 2024

3.5.0 ( 2.13), September 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++

C++, Go

Scala

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Illumos
Linux
OS X
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Natural

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
Go
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

in Natural

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

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

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

by means of logfiles and checkpoints

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)

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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