DBMS > Ingres vs. Machbase Neo vs. Microsoft Azure Synapse Analytics vs. Splice Machine vs. Tarantool

System Properties Comparison Ingres vs. Machbase Neo vs. Microsoft Azure Synapse Analytics vs. Splice Machine vs. Tarantool

Editorial information provided by DB-Engines

Name

Description

Well established RDBMS

TimeSeries DBMS for AIoT and BigData

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	3.63
Rank	#79	Overall
	#43	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Website

www.actian.com/databases/ingres

machbase.com

azure.microsoft.com/services/synapse-analytics

splicemachine.com

www.tarantool.io

Technical documentation

docs.actian.com/ingres

machbase.com/dbms

docs.microsoft.com/azure/synapse-analytics

splicemachine.com/how-it-works

www.tarantool.io/en/doc

Developer

Actian Corporation

Machbase

Microsoft

Splice Machine

Initial release

1974

originally developed at University Berkely in early 1970s

2013

2016

2014

2008

Current release

12.0, July 2024

V8.0, August 2023

3.1, March 2021

2.10.0, May 2022

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

C++

Java

C and C++

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
macOS
Windows

hosted

Linux
OS X
Solaris
Windows

BSD
Linux
macOS

Data scheme

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

Full-featured ANSI SQL support

APIs and other access methods

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Open binary protocol

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C#
Java
PHP

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

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

Transact SQL

yes

Java

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Sharding, horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

selectable replication factor

yes

Multi-source replication
Source-replica replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

yes, multi-version concurrency control (MVCC)

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

volatile and lookup table

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

yes

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

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

show all

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