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DBMS > Apache Impala vs. BigObject vs. Prometheus vs. Tarantool

System Properties Comparison Apache Impala vs. BigObject vs. Prometheus vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBigObject  Xexclude from comparisonPrometheus  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAnalytic DBMS for real-time computations and queriesOpen-source Time Series DBMS and monitoring systemIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websiteimpala.apache.orgbigobject.ioprometheus.iowww.tarantool.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.bigobject.ioprometheus.io/­docswww.tarantool.io/­en/­doc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBigObject, Inc.VK
Initial release2013201520152008
Current release4.1.0, June 20222.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community edition availableOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoC and C++
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
Windows
BSD
Linux
macOS
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesNumeric data onlystring, double, decimal, uuid, integer, blob, boolean, datetime
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.nonono infoImport of XML data possibleno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsnoFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
fluentd
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIOpen binary protocol
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceLuanoLua, C and SQL stored procedures
Triggersnononoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyes infoby FederationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynonenoneCasual 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
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnonoAccess 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
Apache ImpalaBigObjectPrometheusTarantool
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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