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DBMS > Apache Doris vs. Netezza vs. Tarantool vs. Titan

System Properties Comparison Apache Doris vs. Netezza vs. Tarantool vs. Titan

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonTarantool  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolData warehouse and analytics appliance part of IBM PureSystemsIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Graph DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#235  Overall
#110  Relational DBMS
Score7.56
Rank#48  Overall
#31  Relational DBMS
Score1.63
Rank#139  Overall
#25  Document stores
#24  Key-value stores
#65  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.ibm.com/­products/­netezzawww.tarantool.iogithub.com/­thinkaurelius/­titan
Technical documentationgithub.com/­apache/­doris/­wikiwww.tarantool.io/­en/­docgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation, originally contributed from BaiduIBMVKAurelius, owned by DataStax
Initial release2017200020082012
Current release1.2.2, February 20232.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java
Server operating systemsLinuxLinux infoincluded in applianceBSD
Linux
macOS
Linux
OS X
Unix
Windows
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyesFull-featured ANSI SQL supportno
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
OLE DB
Open binary protocolJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesJavaC
C++
Fortran
Java
Lua
Perl
Python
R
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Clojure
Java
Python
Server-side scripts infoStored proceduresuser defined functionsyesLua, C and SQL stored proceduresyes
Triggersnonoyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.yes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
User authentification and security via Rexster Graph Server

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More resources
Apache DorisNetezza infoAlso called PureData System for Analytics by IBMTarantoolTitan
DB-Engines blog posts

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

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Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Apache Doris Analytical Database Graduates from Apache Incubator
20 June 2022, Datanami

StarRocks’ real-time analytics engine moves to the cloud
14 July 2022, SiliconANGLE News

provided by Google News

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, Microsoft

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

provided by Google News

Deploying Tarantool Cartridge applications with zero effort (Part 1)
16 December 2019, Хабр

VShard — horizontal scaling in Tarantool
7 March 2019, Хабр

Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel
18 December 2019, Хабр

provided by Google News

DataStax Acquires Aurelius and its TitanDB Graph Database
31 May 2024, Data Center Knowledge

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database
24 August 2015, AWS Blog

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

Beyond Titan: The Evolution of DataStax’s New Graph Database
21 June 2016, Datanami

provided by Google News



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